The survey on the computer vision works under the adverse weather conditions
| Emoji | Description |
|---|---|
| π· | Single Image |
| πΉ | Video-based |
| π°οΈ | Remote Sensing Data |
| π | Night |
| π | Benchmark |
Venue Abbreviation (click to expand)
- Conference:
| Abbreviation | Full Name |
|---|---|
| CVPR | Computer Vision and Pattern Recognition |
| ICCV | International Conference on Computer Vision |
| ECCV | European Conference on Computer Vision |
| AAAI | AAAI Conference on Artificial Intelligence |
| ICASSP | IEEE International Conference on Acoustics, Speech, and Signal Processing |
| WACV | IEEE Winter Conference on Applications of Computer Vision |
| ICAR | IEEE International Conference on Robotics and Automation |
| ACCV | Asian Conference on Computer Vision |
| ACPR | Asian Conference on Pattern Recognition |
| ISM | IEEE International Symposium on Multimedia |
| ICIP | IEEE International Conference on Image Processing |
| CVM | Computational Visual Media |
| ICTC | International Conference on Information and Communication Technology Convergence |
| ITSC | IEEE International Intelligent Transportation Systems Conference |
- Journal:
| Abbreviation | Full Name |
|---|---|
| TOG | ACM Transactions on Graphics |
| TPAMI | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| IJCV | International Journal of Computer Vision |
| TIP | IEEE Transactions on Image Processing |
| TCSVT | IEEE Transactions on Circuits and Systems for Video Technology |
| TIM | IEEE Transactions on Instrumentation and Measurement |
| TCI | IEEE Transactions on Computational Imaging |
| ARCME | Archives of Computational Methods in Engineering |
| OE | Optical Engineering |
| Opt. Express | Optics Express |
-
Low-level Vision
Β Β Β Β π«οΈ Haze removal / Fog Removal / Dehazing / Defogging
Β Β Β Β π§οΈ Rain removal / Deraining / De-raining
Β Β Β Β Β Β Β Β β Rain Streak Removal
Β Β Β Β Β Β Β Β π§ Raindrop Removal
Β Β Β Β βοΈ Snow Removal / Desnowing / De-snowing
Β Β Β Β All-in-One (AiO) Adverse Weather Removal -
High-level Vision
Β Β Β Β Object Detection
Β Β Β Β Semantic Segmentation
Β Β Β Β Object Tracking
Β Β Β Β Depth Estimation
Β Β Β Β Autonomous Driving
Β Β Β Β Scene Stylization
| Paper | Venue | Year | Data | Link | Code |
|---|---|---|---|---|---|
| A comprehensive review of computational dehazing techniques |
ARCME | 2018 | π· | Paper | |
| A survey on all-in-one image restoration: Taxonomy, evaluation and future trends |
TPAMI | 2025 | π· | Paper | Code |
Paper List (click to expand)
| Paper | Venue | Year | Data | Method | Link | Code |
|---|---|---|---|---|---|---|
| Visibility in bad weather from a single image Robby T. Tan |
CVPR | 2008 | π· | Model-based | Paper | Code |
| Benchmarking single-image dehazing and beyond Boyi Li; Wenqi Ren; Dengpan Fu; Dacheng Tao; Dan Feng; Wenjun Zeng |
TIP | 2018 | π·π | Paper | Code | |
| Single image dehazing Raanan Fattal |
TOG | 2008 | π· | Model-based | Paper | Code |
| Enhanced pix2pix dehazing network Yanyun Qu; Yizi Chen; Jingying Huang; Yuan Xie |
CVPR | 2019 | π· | CNN | Paper | Code |
| Contrastive learning for compact single image dehazing |
2021 | π· | Paper | |||
| Non-local image dehazing |
2016 | π· | Paper | |||
| Vision transformers for single image dehazing |
2023 | π· | Paper | |||
| Cycle-dehaze: Enhanced cyclegan for single image dehazing |
2018 | π· | Paper | |||
| Single image dehazing by multi-scale fusion |
2013 | π· | Paper | |||
| Dehazing using color-lines |
TOG | 2014 | π· | Model-based | Paper | Code |
| A comprehensive review on analysis and implementation of recent image dehazing methods |
2022 | π· | Paper | |||
| Single image dehazing via multi-scale convolutional neural networks |
2016 | π· | Paper | |||
| A review of remote sensing image dehazing |
2021 | π· | Paper | |||
| Aod-net: All-in-one dehazing network |
2017 | π· | Paper | |||
| An all-in-one network for dehazing and beyond |
1707 | π· | Paper | |||
| An investigation of dehazing effects on image and video coding |
2011 | πΉ | Paper | |||
| Griddehazenet: Attention-based multi-scale network for image dehazing |
2019 | π· | Paper | |||
| Fast image dehazing method based on linear transformation |
2017 | π· | Paper | |||
| Domain adaptation for image dehazing |
2020 | π· | Paper | |||
| Perceiving and modeling density for image dehazing |
2022 | π· | Paper | |||
| Densely connected pyramid dehazing network |
2018 | π· | Paper | |||
| Single remote sensing image dehazing |
2013 | π· | Paper | |||
| Single image dehazing using haze-lines |
2018 | π· | Paper | |||
| D-hazy: A dataset to evaluate quantitatively dehazing algorithms |
2016 | π· | Paper | |||
| Recent advances in image dehazing |
2017 | π· | Paper | |||
| Gated fusion network for single image dehazing |
2018 | π· | Paper | |||
| Dehazegan: When image dehazing meets differential programming. |
2018 | π· | Paper | |||
| Semi-supervised image dehazing |
2019 | π· | Paper | |||
| Instant dehazing of images using polarization |
2001 | π· | Paper | |||
| Single image dehazing based on the physical model and MSRCR algorithm |
2017 | π· | Paper | |||
| Trident dehazing network |
2020 | π· | Paper | |||
| Review of dehazing techniques: challenges and future trends |
2025 | π· | Paper | |||
| Investigating haze-relevant features in a learning framework for image dehazing |
2014 | π· | Paper | |||
| Single image dehazing using saturation line prior |
2023 | π· | Paper | |||
| EENet: An effective and efficient network for single image dehazing |
2025 | π· | Paper | |||
| Efficient image dehazing with boundary constraint and contextual regularization |
2013 | π· | Paper | |||
| Quality evaluation of image dehazing methods using synthetic hazy images |
2019 | π· | Paper | |||
| Single image dehazing via conditional generative adversarial network |
2018 | π· | Paper | |||
| Initial results in underwater single image dehazing |
2010 | π· | Paper | |||
| Frequency and spatial dual guidance for image dehazing |
2022 | π· | Paper | |||
| End-to-end united video dehazing and detection |
2018 | πΉ | Paper | |||
| Dehazing evaluation: Real-world benchmark datasets, criteria, and baselines |
2020 | π· | Paper | |||
| Single image dehazing using ranking convolutional neural network |
2017 | π· | Paper | |||
| Rethinking performance gains in image dehazing networks |
2209 | π· | Paper | |||
| Learning deep priors for image dehazing |
2019 | π· | Paper | |||
| FAMED-Net: A fast and accurate multi-scale end-to-end dehazing network |
2019 | π· | Paper | |||
| A comparative study of image dehazing algorithms |
2020 | π· | Paper | |||
| Color image dehazing using the near-infrared |
2009 | π· | Paper | |||
| Image dehazing using polarization effects of objects and airlight |
2014 | π· | Paper | |||
| An iterative image dehazing method with polarization |
2018 | π· | Paper | |||
| Effective single image dehazing by fusion |
2010 | π· | Paper | |||
| Perceptual evaluation of single image dehazing algorithms |
2015 | π· | Paper | |||
| Curricular contrastive regularization for physics-aware single image dehazing |
2023 | π· | Paper | |||
| Zero-shot image dehazing |
2020 | π· | Paper | |||
| Light-DehazeNet: a novel lightweight CNN architecture for single image dehazing |
2021 | π· | Paper | |||
| Image dehazing using residual-based deep CNN |
2018 | π· | Paper | |||
| A fast image dehazing algorithm using morphological reconstruction |
2018 | π· | Paper | |||
| Efficient single image dehazing and denoising: An efficient multi-scale correlated wavelet approach |
2017 | π· | Paper | |||
| A review on dark channel prior based image dehazing algorithms |
2016 | π· | Paper | |||
| Physics-based feature dehazing networks |
2020 | π· | Paper | |||
| Deep video dehazing with semantic segmentation |
2018 | πΉ | Paper | |||
| Hazerd: an outdoor scene dataset and benchmark for single image dehazing |
2017 | π· | Paper | |||
| U-shaped vision mamba for single image dehazing |
2402 | π· | Paper | |||
| FFA-Net: Feature fusion attention network for single image dehazing |
2020 | π· | Paper | |||
| O-haze: a dehazing benchmark with real hazy and haze-free outdoor images |
2018 | π· | Paper | |||
| Image dehazing transformer with transmission-aware 3d position embedding |
2022 | π· | Paper | |||
| Single image dehazing based on contrast enhancement |
2011 | π· | Paper | |||
| RefineDNet: A weakly supervised refinement framework for single image dehazing |
2021 | π· | Paper | |||
| Underwater image enhancement by wavelength compensation and dehazing |
2011 | π· | Paper | |||
| Knowledge transfer dehazing network for nonhomogeneous dehazing |
2020 | π· | Paper | |||
| Near-infrared guided color image dehazing |
2013 | π· | Paper | |||
| A review on intelligence dehazing and color restoration for underwater images |
2018 | π· | Paper | |||
| UCL-dehaze: Toward real-world image dehazing via unsupervised contrastive learning |
2024 | π· | Paper | |||
| Enhanced variational image dehazing |
2015 | π· | Paper | |||
| Optimized contrast enhancement for real-time image and video dehazing |
2013 | πΉ | Paper | |||
| Multi-scale boosted dehazing network with dense feature fusion |
2020 | π· | Paper | |||
| Deep multi-model fusion for single-image dehazing |
2019 | π· | Paper | |||
| Image dehazing by artificial multiple-exposure image fusion |
2018 | π· | Paper | |||
| A survey of image dehazing approaches |
2015 | π· | Paper | |||
| Depth information assisted collaborative mutual promotion network for single image dehazing |
2024 | π· | Paper | |||
| IDGCP: Image dehazing based on gamma correction prior |
2019 | π· | Paper | |||
| You only look yourself: Unsupervised and untrained single image dehazing neural network |
2021 | π· | Paper | |||
| Mixdehazenet: Mix structure block for image dehazing network |
2024 | π· | Paper | |||
| IDRLP: Image dehazing using region line prior |
2021 | π· | Paper | |||
| Night-time dehazing by fusion |
2016 | π· | Paper | |||
| Detection-friendly dehazing: Object detection in real-world hazy scenes |
2023 | π· | Paper | |||
| Self-guided image dehazing using progressive feature fusion |
2022 | π· | Paper | |||
| Ridcp: Revitalizing real image dehazing via high-quality codebook priors |
2023 | π· | Paper | |||
| On the duality between retinex and image dehazing |
2018 | π· | Paper | |||
| From synthetic to real: Image dehazing collaborating with unlabeled real data |
2021 | π· | Paper | |||
| A comprehensive survey and taxonomy on single image dehazing based on deep learning |
2023 | π· | Paper | |||
| Single image dehazing using color ellipsoid prior |
2017 | π· | Paper | |||
| A cascaded convolutional neural network for single image dehazing |
2018 | π· | Paper | |||
| Single image dehazing through improved atmospheric light estimation |
2016 | π· | Paper | |||
| Improved wavelet transform algorithm for single image dehazing |
2014 | π· | Paper | |||
| Uncertainty-driven dehazing network |
2022 | π· | Paper | |||
| Ultra-high-definition image dehazing via multi-guided bilateral learning |
2021 | π· | Paper | |||
| Multi-scale single image dehazing using perceptual pyramid deep network |
2018 | π· | Paper | |||
| Single image dehazing via multi-scale convolutional neural networks with holistic edges |
2020 | π· | Paper | |||
| Single image dehazing using color attenuation prior. |
2014 | π· | Paper | |||
| Progressive feature fusion network for realistic image dehazing |
2018 | π· | Paper | |||
| Advancing real-world image dehazing: Perspective, modules, and training |
2024 | π· | Paper | |||
| Fusion-based variational image dehazing |
2016 | π· | Paper | |||
| Self-augmented unpaired image dehazing via density and depth decomposition |
2022 | π· | Paper | |||
| Image dehazing via enhancement, restoration, and fusion: A survey |
2022 | π· | Paper | |||
| Improved single image dehazing using geometry |
2009 | π· | Paper | |||
| Fast image dehazing using guided joint bilateral filter |
2012 | π· | Paper | |||
| PDR-Net: Perception-inspired single image dehazing network with refinement |
2019 | π· | Paper | |||
| A novel fast single image dehazing algorithm based on artificial multiexposure image fusion |
2020 | π· | Paper | |||
| Multi-scale optimal fusion model for single image dehazing |
2019 | π· | Paper | |||
| Single image dehazing with a generic model-agnostic convolutional neural network |
2019 | π· | Paper | |||
| LIDN: a novel light invariant image dehazing network |
2023 | π· | Paper | |||
| Proximal dehaze-net: A prior learning-based deep network for single image dehazing |
2018 | π· | Paper | |||
| Single image dehazing using a multilayer perceptron |
2018 | π· | Paper | |||
| Gated context aggregation network for image dehazing and deraining |
2019 | π· | Paper | |||
| PSD: Principled synthetic-to-real dehazing guided by physical priors |
2021 | π· | Paper | |||
| Blind dehazing using internal patch recurrence |
2016 | π· | Paper | |||
| Video dehazing with spatial and temporal coherence |
2011 | πΉ | Paper | |||
| Single image dehazing using improved cycleGAN |
2021 | π· | Paper | |||
| Recent advances in image dehazing: Formal analysis to automated approaches |
2024 | π· | Paper | |||
| ICycleGAN: Single image dehazing based on iterative dehazing model and CycleGAN |
2021 | π· | Paper | |||
| Fast single image dehazing using saturation based transmission map estimation |
2019 | π· | Paper | |||
| Single image dehazing using a new color channel |
2021 | π· | Paper | |||
| Real-time dehazing for image and video |
2010 | πΉ | Paper | |||
| AIPNet: Image-to-image single image dehazing with atmospheric illumination prior |
2018 | π· | Paper | |||
| I-HAZE: A dehazing benchmark with real hazy and haze-free indoor images |
2018 | π· | Paper | |||
| AED-Net: A single image dehazing |
2022 | π· | Paper | |||
| NH-HAZE: An image dehazing benchmark with non-homogeneous hazy and haze-free images |
2020 | π· | Paper | |||
| Fast image dehazing using improved dark channel prior |
2012 | π· | Paper | |||
| Fsad-net: feedback spatial attention dehazing network |
2022 | π· | Paper | |||
| Towards domain invariant single image dehazing |
2021 | π· | Paper | |||
| DEA-Net: Single image dehazing based on detail-enhanced convolution and content-guided attention |
2024 | π· | Paper | |||
| LKD-Net: Large kernel convolution network for single image dehazing |
2023 | π· | Paper | |||
| Mb-taylorformer: Multi-branch efficient transformer expanded by taylor formula for image dehazing |
2023 | π· | Paper | |||
| IDE: Image dehazing and exposure using an enhanced atmospheric scattering model |
2021 | π· | Paper | |||
| A fast image dehazing algorithm based on negative correction |
2014 | π· | Paper | |||
| Single image dehazing with an independent detail-recovery network |
2022 | π· | Paper | |||
| DRCDN: learning deep residual convolutional dehazing networks |
2020 | π· | Paper | |||
| Single image dehazing with a physical model and dark channel prior |
2015 | π· | Paper | |||
| Distilling image dehazing with heterogeneous task imitation |
2020 | π· | Paper | |||
| Single image dehazing using deep neural networks |
2019 | π· | Paper | |||
| Multi-level feature interaction and efficient non-local information enhanced channel attention for image dehazing |
2023 | π· | Paper | |||
| Unsupervised multi-branch network with high-frequency enhancement for image dehazing |
2024 | π· | Paper | |||
| Dehazing for images with large sky region |
2017 | π· | Paper | |||
| Single image dehazing using the change of detail prior |
2015 | π· | Paper | |||
| Color channel transfer for image dehazing |
2019 | π· | Paper | |||
| Progressive negative enhancing contrastive learning for image dehazing and beyond |
2024 | π· | Paper | |||
| Delving deeper into image dehazing: A survey |
2023 | π· | Paper | |||
| Pyramid global context network for image dehazing |
2020 | π· | Paper | |||
| QCNN-H: Single-image dehazing using quaternion neural networks |
2023 | π· | Paper | |||
| Day and night-time dehazing by local airlight estimation |
2020 | π· | Paper | |||
| Dense-haze: A benchmark for image dehazing with dense-haze and haze-free images |
2019 | π· | Paper | |||
| Dehazing for multispectral remote sensing images based on a convolutional neural network with the residual architecture |
2018 | π· | Paper | |||
| Single image dehazing using CNN |
2019 | π· | Paper | |||
| Generative adversarial and self-supervised dehazing network |
2023 | π· | Paper | |||
| IDeRs: Iterative dehazing method for single remote sensing image |
2019 | π· | Paper | |||
| Dual-scale single image dehazing via neural augmentation |
2022 | π· | Paper | |||
| Single image dehazing via NIN-DehazeNet |
2019 | π· | Paper | |||
| A database with reference for image dehazing evaluation |
2018 | π· | Paper | |||
| USID-Net: Unsupervised single image dehazing network via disentangled representations |
2022 | π· | Paper | |||
| A novel bi-stream network for image dehazing |
2024 | π· | Paper | |||
| Underwater image dehazing using joint trilateral filter |
2014 | π· | Paper | |||
| Deep retinex network for single image dehazing |
2020 | π· | Paper | |||
| A comprehensive survey on image dehazing for different atmospheric scattering models |
2024 | π· | Paper | |||
| Nighttime dehazing with a synthetic benchmark |
2020 | π· | Paper | |||
| Joint transmission map estimation and dehazing using deep networks |
2019 | π· | Paper | |||
| High-quality image dehazing with diffusion model |
2308 | π· | Paper | |||
| Trinity-net: Gradient-guided swin transformer-based remote sensing image dehazing and beyond |
2023 | π· | Paper | |||
| Improved single image dehazing using segmentation |
2010 | π· | Paper | |||
| Image dehazing using deep learning techniques |
2020 | π· | Paper | |||
| Deep learning based single image dehazing |
2018 | π· | Paper | |||
| Towards compact single image dehazing via task-related contrastive network |
2024 | π· | Paper | |||
| A region-wised medium transmission based image dehazing method |
2017 | π· | Paper | |||
| Deep hybrid model for single image dehazing and detail refinement |
2023 | π· | Paper | |||
| Multi-scale single image dehazing using Laplacian and Gaussian pyramids |
2021 | π· | Paper | |||
| PhDnet: A novel physic-aware dehazing network for remote sensing images |
2024 | π· | Paper | |||
| Frequency compensated diffusion model for real-scene dehazing |
2024 | π· | Paper | |||
| Image dehazing by an artificial image fusion method based on adaptive structure decomposition |
2020 | π· | Paper | |||
| DENSE123'COLOR Enhancement Dehazing Network |
2019 | π· | Paper | |||
| Unsupervised single image dehazing using dark channel prior loss |
2019 | π· | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Data | Metohd | Link | Code |
|---|---|---|---|---|---|---|
| Progressive image deraining networks: A better and simpler baseline |
2019 | π· | Paper | |||
| Single image deraining: From model-based to data-driven and beyond |
2020 | π· | Paper | |||
| Data-driven single image deraining: A comprehensive review and new perspectives |
2023 | π· | Paper | |||
| Single image deraining: A comprehensive benchmark analysis |
2019 | π· | Paper | |||
| Multi-scale progressive fusion network for single image deraining |
2020 | π· | Paper | |||
| Learning a sparse transformer network for effective image deraining |
2023 | π· | Paper | |||
| Towards unified deep image deraining: A survey and a new benchmark |
2025 | π· | Paper | |||
| Residual-guide network for single image deraining |
2018 | π· | Paper | |||
| Detail-recovery image deraining via context aggregation networks |
2020 | π· | Paper | |||
| Spatial attentive single-image deraining with a high quality real rain dataset |
2019 | π· | Paper | |||
| Conditional variational image deraining |
2020 | π· | Paper | |||
| Lightweight pyramid networks for image deraining |
2019 | π· | Paper | |||
| Single image deraining using bilateral recurrent network |
2020 | π· | Paper | |||
| Variational image deraining |
2020 | π· | Paper | |||
| Freqmamba: Viewing mamba from a frequency perspective for image deraining |
2024 | π· | Paper | |||
| Syn2real transfer learning for image deraining using gaussian processes |
2020 | π· | Paper | |||
| A comprehensive benchmark analysis of single image deraining: Current challenges and future perspectives |
2021 | π· | Paper | |||
| Multi-scale fusion and decomposition network for single image deraining |
2023 | π· | Paper | |||
| Robust representation learning with feedback for single image deraining |
2021 | π· | Paper | |||
| Video desnowing and deraining based on matrix decomposition |
2017 | πΉ | Paper | |||
| Smartassign: Learning a smart knowledge assignment strategy for deraining and desnowing |
2023 | π· | Paper | |||
| Unpaired deep image deraining using dual contrastive learning |
2022 | π· | Paper | |||
| Semi-deraingan: A new semi-supervised single image deraining network |
2020 | π· | Paper | |||
| Beyond monocular deraining: Stereo image deraining via semantic understanding |
2020 | π· | Paper | |||
| Rethinking multi-scale representations in deep deraining transformer |
2024 | π· | Paper | |||
| Gated context aggregation network for image dehazing and deraining |
2019 | π· | Paper | |||
| Recurrent squeeze-and-excitation context aggregation net for single image deraining |
2018 | π· | Paper | |||
| Multi-scale hybrid fusion network for single image deraining |
2021 | π· | Paper | |||
| Efficientderain: Learning pixel-wise dilation filtering for high-efficiency single-image deraining |
2021 | π· | Paper | |||
| Beyond monocular deraining: Parallel stereo deraining network via semantic prior |
2022 | π· | Paper | |||
| Etdnet: An efficient transformer deraining model |
2021 | π· | Paper | |||
| Unsupervised deraining: Where contrastive learning meets self-similarity |
2022 | π· | Paper | |||
| Deraincyclegan: Rain attentive cyclegan for single image deraining and rainmaking |
2021 | π· | Paper | |||
| Unsupervised single image deraining with self-supervised constraints |
2019 | π· | Paper | |||
| Memory oriented transfer learning for semi-supervised image deraining |
2021 | π· | Paper | |||
| Rethinking image deraining via rain streaks and vapors |
2020 | π· | Paper | |||
| Dreaming to prune image deraining networks |
2022 | π· | Paper | |||
| FMRNet: Image deraining via frequency mutual revision |
2024 | π· | Paper | |||
| Hybrid cnn-transformer feature fusion for single image deraining |
2023 | π· | Paper | |||
| Residual multiscale based single image deraining |
2019 | π· | Paper | |||
| Sginet: Toward sufficient interaction between single image deraining and semantic segmentation |
2022 | π· | Paper | |||
| Drt: A lightweight single image deraining recursive transformer |
2022 | π· | Paper | |||
| Not just streaks: Towards ground truth for single image deraining |
2022 | π· | Paper | |||
| Networks are slacking off: Understanding generalization problem in image deraining |
2023 | π· | Paper | |||
| Semi-supervised image deraining using knowledge distillation |
2022 | π· | Paper | |||
| Continual image deraining with hypergraph convolutional networks |
2023 | π· | Paper | |||
| Bidirectional multi-scale implicit neural representations for image deraining |
2024 | π· | Paper | |||
| Memory uncertainty learning for real-world single image deraining |
2022 | π· | Paper | |||
| Single-image deraining using an adaptive nonlocal means filter |
2013 | π· | Paper | |||
| A two-stage density-aware single image deraining method |
2021 | π· | Paper | |||
| Single image deraining via recurrent hierarchy enhancement network |
2019 | π· | Paper | |||
| A coarse-to-fine multi-stream hybrid deraining network for single image deraining |
2019 | π· | Paper | |||
| Frame-consistent recurrent video deraining with dual-level flow |
2019 | πΉ | Paper | |||
| Rain-free and residue hand-in-hand: A progressive coupled network for real-time image deraining |
2021 | π· | Paper | |||
| Danet: Image deraining via dynamic association learning. |
2022 | π· | Paper | |||
| Efficient frequency-domain image deraining with contrastive regularization |
2024 | π· | Paper | |||
| Learning a spiking neural network for efficient image deraining |
2024 | π· | Paper | |||
| Towards ultra-high-definition image deraining: A benchmark and an efficient method |
2024 | π· | Paper | |||
| Physical model guided deep image deraining |
2003 | π· | Paper | |||
| Toward real-world single image deraining: A new benchmark and beyond |
2022 | π· | Paper | |||
| PFDN: Pyramid feature decoupling network for single image deraining |
2022 | π· | Paper | |||
| Decomposition makes better rain removal: An improved attention-guided deraining network |
2020 | π· | Paper | |||
| A hybrid transformer-mamba network for single image deraining |
2024 | π· | Paper | |||
| A comprehensive survey: Image deraining and stereoβmatching taskβdriven performance analysis |
2022 | π· | Paper | |||
| Semi-supervised image deraining using gaussian processes |
2021 | π· | Paper | |||
| Multi-decoding deraining network and quasi-sparsity based training |
2021 | π· | Paper | |||
| Learning rain location prior for nighttime deraining |
2023 | π· | Paper | |||
| DECTNet: A detail enhanced CNN-Transformer network for single-image deraining |
2025 | π· | Paper | |||
| Single-image deraining via recurrent residual multiscale networks |
2020 | π· | Paper | |||
| Rainmamba: Enhanced locality learning with state space models for video deraining |
2024 | πΉ | Paper | |||
| Unpaired learning for deep image deraining with rain direction regularizer |
2021 | π· | Paper | |||
| Progressive network based on detail scaling and texture extraction: A more general framework for image deraining |
2024 | π· | Paper | |||
| SDNet: mutil-branch for single image deraining using swin |
2021 | π· | Paper | |||
| Fouriermamba: Fourier learning integration with state space models for image deraining |
2405 | π· | Paper | |||
| Mffdnet: Single image deraining via dual-channel mixed feature fusion |
2024 | π· | Paper | |||
| Structure-preserving deraining with residue channel prior guidance |
2021 | π· | Paper | |||
| Magic ELF: Image deraining meets association learning and transformer |
2022 | π· | Paper | |||
| Scale-free single image deraining via visibility-enhanced recurrent wavelet learning |
2019 | π· | Paper | |||
| Single image deraining using scale-aware multi-stage recurrent network |
1712 | π· | Paper | |||
| Intensity-aware single-image deraining with semantic and color regularization |
2021 | π· | Paper | |||
| Dilated convolutional transformer for high-quality image deraining |
2023 | π· | Paper | |||
| Wavelet approximation-aware residual network for single image deraining |
2023 | π· | Paper | |||
| Semi-supervised video deraining with dynamical rain generator |
2021 | πΉ | Paper | |||
| Exploring overcomplete representations for single image deraining using cnns |
2020 | π· | Paper | |||
| Fastderainnet: A deep learning algorithm for single image deraining |
2020 | π· | Paper | |||
| DPNet: Detail-preserving image deraining via learning frequency domain knowledge |
2022 | π· | Paper | |||
| Image deraining via invertible disentangled representations |
2024 | π· | Paper | |||
| Deep scale-space mining network for single image deraining |
2022 | π· | Paper | |||
| Nasnet: A neuron attention stage-by-stage net for single image deraining |
1912 | π· | Paper | |||
| Unsupervised image deraining: Optimization model driven deep cnn |
2021 | π· | Paper | |||
| Residual-guide feature fusion network for single image deraining |
1804 | π· | Paper | |||
| Semi-swinderain: Semi-supervised image deraining network using swin transformer |
2023 | π· | Paper | |||
| Unsupervised video deraining with an event camera |
2023 | πΉ | Paper | |||
| DerainGAN: Single image deraining using wasserstein GAN |
2021 | π· | Paper | |||
| Enhanced spatio-temporal interaction learning for video deraining: faster and better |
2022 | πΉ | Paper | |||
| Recurrent multi-frame deraining: Combining physics guidance and adversarial learning |
2021 | π· | Paper | |||
| Context-enhanced representation learning for single image deraining |
2021 | π· | Paper | |||
| Single image deraining using time-lapse data |
2020 | π· | Paper | |||
| Utilizing two-phase processing with FBLS for single image deraining |
2020 | π· | Paper | |||
| SAPNet: Segmentation-aware progressive network for perceptual contrastive deraining |
2022 | π· | Paper | |||
| Dawn: Direction-aware attention wavelet network for image deraining |
2023 | π· | Paper | |||
| Selective wavelet attention learning for single image deraining |
2021 | π· | Paper | |||
| DSDNet: Toward single image deraining with self-paced curricular dual stimulations |
2023 | π· | Paper | |||
| Dual heterogeneous complementary networks for single image deraining |
2022 | π· | Paper | |||
| Single image deraining with continuous rain density estimation |
2021 | π· | Paper | |||
| Video deraining and desnowing using temporal correlation and low-rank matrix completion |
2015 | πΉ | Paper | |||
| Image deraining with frequency-enhanced state space model |
2024 | π· | Paper | |||
| DRD-Net: Detail-recovery image deraining via context aggregation networks |
2019 | π· | Paper | |||
| Context-detail-aware united network for single image deraining |
2024 | π· | Paper | |||
| Online-updated high-order collaborative networks for single image deraining |
2022 | π· | Paper | |||
| An end-to-end cascaded image deraining and object detection neural network |
2022 | π· | Paper | |||
| RCDNet: An interpretable rain convolutional dictionary network for single image deraining |
2023 | π· | Paper | |||
| A two-stage network with wavelet transformation for single-image deraining |
2023 | π· | Paper | |||
| Explore internal and external similarity for single image deraining with graph neural networks |
2406 | π· | Paper | |||
| Single image deraining network with rain embedding consistency and layered LSTM |
2022 | π· | Paper | |||
| Image Deraining via Self-supervised Reinforcement Learning |
2024 | π· | Paper | |||
| Joint self-attention and scale-aggregation for self-calibrated deraining network |
2020 | π· | Paper | |||
| A novel dual-stage progressive enhancement network for single image deraining |
2024 | π· | Paper | |||
| Deep single image deraining via modeling haze-like effect |
2020 | π· | Paper | |||
| Adaptive Frequency Enhancement Network for Single Image Deraining |
2024 | π· | Paper | |||
| Single image deraining using a recurrent multi-scale aggregation and enhancement network |
2019 | π· | Paper | |||
| Single traffic image deraining via similarity-diversity model |
2023 | π· | Paper | |||
| RealβWorld Image Deraining Using ModelβFree Unsupervised Learning |
2024 | π· | Paper | |||
| RainFormer: a pyramid transformer for single image deraining. |
2023 | π· | Paper | |||
| Wavelet channel attention module with a fusion network for single image deraining |
2020 | π· | Paper | |||
| Nightrain: Nighttime video deraining via adaptive-rain-removal and adaptive-correction |
2024 | πΉ | Paper | |||
| Event-aware video deraining via multi-patch progressive learning |
2023 | πΉ | Paper | |||
| Cross-domain collaborative learning for single image deraining |
2023 | π· | Paper | |||
| Unrolling a rain-guided detail recovery network for singleimage deraining |
2023 | π· | Paper | |||
| Exploring Local Sparse Structure Prior for Image Deraining and Desnowing |
2024 | π· | Paper | |||
| Cycle contrastive adversarial learning with structural consistency for unsupervised high-quality image deraining transformer |
2024 | π· | Paper | |||
| Single image deraining using scale constraint iterative update network |
2024 | π· | Paper | |||
| Recurrent wavelet structure-preserving residual network for single image deraining |
2023 | π· | Paper | |||
| Pixel-wise content attention learning for single-image deraining of autonomous vehicles |
2023 | π· | Paper | |||
| Dual recursive network for fast image deraining |
2019 | π· | Paper | |||
| Unsupervised deraining: Where asymmetric contrastive learning meets self-similarity |
2023 | π· | Paper | |||
| Recovering a clean background: A parallel deep network architecture for single-image deraining |
2024 | π· | Paper | |||
| Event-driven heterogeneous network for video deraining |
2024 | πΉ | Paper | |||
| Meta-learning based relation and representation learning networks for single-image deraining |
2021 | π· | Paper | |||
| Contrastive unfolding deraining network |
2022 | π· | Paper | |||
| Rain2Avoid: Learning Deraining by Self-Supervision |
2025 | π· | Paper | |||
| Self-aligned video deraining with transmission-depth consistency |
2021 | πΉ | Paper | |||
| Progressive subtractive recurrent lightweight network for video deraining |
2021 | πΉ | Paper | |||
| Close the loop: A unified bottom-up and top-down paradigm for joint image deraining and segmentation |
2022 | π· | Paper | |||
| Image deraining transformer with sparsity and frequency guidance |
2023 | π· | Paper | |||
| Image de-raining using a conditional generative adversarial network |
2019 | π· | Paper | |||
| Single-image deraining via a recurrent memory unit network |
2021 | π· | Paper | |||
| UC-former: A multi-scale image deraining network using enhanced transformer |
2024 | π· | Paper | |||
| Image de-raining transformer |
2022 | π· | Paper | |||
| Ultra-Fast Deraining Plugin for Vision-Based Perception of Autonomous Driving |
2024 | π· | Paper | |||
| Ensemble single image deraining network via progressive structural boosting constraints |
2021 | π· | Paper | |||
| Hpcnet: A hybrid progressive coupled network for image deraining |
2023 | π· | Paper | |||
| Synthesized rain images for deraining algorithms |
2022 | π· | Paper | |||
| Model-based deep network for single image deraining |
2020 | π· | Paper | |||
| Local and global knowledge distillation with direction-enhanced contrastive learning for single-image deraining |
2023 | π· | Paper | |||
| EfficientDeRain+: Learning Uncertainty-Aware Filtering via RainMix Augmentation for High-Efficiency Deraining |
2025 | π· | Paper | |||
| FoNet: Focused network for single image deraining |
2025 | π· | Paper | |||
| Distributed feedback network for single-image deraining |
2021 | π· | Paper | |||
| High-level task-driven single image deraining: Segmentation in rainy days |
2020 | π· | Paper | |||
| From coarse to fine: A stage-wise deraining net |
2019 | π· | Paper | |||
| Pearl: Preprocessing enhanced adversarial robust learning of image deraining for semantic segmentation |
2023 | π· | Paper | |||
| Triple-level model inferred collaborative network architecture for video deraining |
2021 | πΉ | Paper | |||
| Neural SchrΓΆdinger bridge for unpaired real-world image deraining |
2024 | π· | Paper | |||
| Aggregating global and local representations via hybrid transformer for video deraining |
2024 | πΉ | Paper | |||
| Single image deraining via deep shared pyramid network |
2021 | π· | Paper | |||
| A convolutional network for joint deraining and dehazing from a single image for autonomous driving in rain |
2019 | π· | Paper | |||
| Alternating attention transformer for single image deraining |
2023 | π· | Paper | |||
| Rethinking image deraining via text-guided detail reconstruction |
2024 | π· | Paper | |||
| Deep image deraining |
2023 | π· | Paper | |||
| GKC-Net: gated KAN with Channel-Position attention mechanism for image deraining |
2026 | π· | Paper | |||
| Rethinking video rain streak removal: A new synthesis model and a deraining network with video rain prior |
2022 | πΉ | Paper | |||
| A framework of single-image deraining method based on analysis of rain characteristics |
2016 | π· | Paper | |||
| Single image deraining via decorrelating the rain streaks and background scene in gradient domain |
2018 | π· | Paper | |||
| Pixel Adaptive Deep Unfolding Network with State Space Model for Image Deraining |
2025 | π· | Paper | |||
| Image deraining algorithm based on multi-scale features |
2024 | π· | Paper | |||
| Multi-scale hourglass hierarchical fusion network for single image deraining |
2021 | π· | Paper | |||
| A single image deraining algorithm guided by text generation based on depth information conditions |
2025 | π· | Paper | |||
| Tpsence: Towards artifact-free realistic rain generation for deraining and object detection in rain |
2024 | π· | Paper | |||
| Fluid: Few-shot self-supervised image deraining |
2022 | π· | Paper | |||
| Unpaired photo-realistic image deraining with energy-informed diffusion model |
2024 | π· | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Data | Link | Code |
|---|
Paper List (click to expand)
| Paper | Venue | Year | Data | Method | Link | Code |
|---|---|---|---|---|---|---|
| Attentive generative adversarial network for raindrop removal from a single image |
2018 | π· | Paper | |||
| Learning from synthetic photorealistic raindrop for single image raindrop removal |
2019 | π· | Paper | |||
| Adherent raindrop modeling, detection and removal in video |
2015 | πΉ | Paper | |||
| Raindrop clarity: A dual-focused dataset for day and night raindrop removal |
2024 | π· | Paper | |||
| Raingan: Unsupervised raindrop removal via decomposition and composition |
2022 | π· | Paper | |||
| Dual attention-in-attention model for joint rain streak and raindrop removal |
2021 | π· | Paper | |||
| Adherent raindrop detection and removal in video |
2013 | πΉ | Paper | |||
| Feature-aligned video raindrop removal with temporal constraints |
2022 | πΉ | Paper | |||
| Dual-pixel raindrop removal |
2024 | π· | Paper | |||
| Uncertainty guided multi-scale attention network for raindrop removal from a single image |
2021 | π· | Paper | |||
| Removing raindrops and rain streaks in one go |
2021 | π· | Paper | |||
| STRRNet: Semantics-guided two-stage raindrop removal network |
2025 | π· | Paper | |||
| Uav-rain1k: A benchmark for raindrop removal from uav aerial imagery |
2024 | π· | Paper | |||
| Raindrop detection and removal from long range trajectories |
2014 | π· | Paper | |||
| Raindrop detection and removal using salient visual features |
2012 | π· | Paper | |||
| UnfairGAN: An enhanced generative adversarial network for raindrop removal from a single image |
2022 | π· | Paper | |||
| Context and detail interaction network for stereo rain streak and raindrop removal |
2023 | π· | Paper | |||
| Joint raindrop and haze removal from a single image |
2020 | π· | Paper | |||
| NTIRE 2025 challenge on day and night raindrop removal for dual-focused images: Methods and results |
2025 | π· | Paper | |||
| Selective generative adversarial network for raindrop removal from a single image |
2021 | π· | Paper | |||
| Weakly supervised learning for raindrop removal on a single image |
2020 | π· | Paper | |||
| A review of detection and removal of raindrops in automotive vision systems |
2021 | π· | Paper | |||
| Adherent raindrop removal with self-supervised attention maps and spatio-temporal generative adversarial networks |
2019 | π· | Paper | |||
| Mask-guided progressive network for joint raindrop and rain streak removal in videos |
2023 | πΉ | Paper | |||
| Raindrop-removal image translation using target-mask network with attention module |
2023 | π· | Paper | |||
| Raindrop removal with light field image using image inpainting |
2020 | π· | Paper | |||
| Laplacian encoder-decoder network for raindrop removal |
2022 | π· | Paper | |||
| Review on raindrop detection and removal in weather degraded images |
2013 | π· | Paper | |||
| Raindrop removal from a single image using a two-step generative adversarial network |
2022 | π· | Paper | |||
| Removal of rain in video based on motion and shape characteristics of raindrops |
2014 | πΉ | Paper | |||
| Adherent mist and raindrop removal from a single image using attentive convolutional network |
2022 | π· | Paper | |||
| Unsupervised Network for Single Image Raindrop Removal |
2412 | π· | Paper | |||
| Robust attention deraining network for synchronous rain streaks and raindrops removal |
2022 | π· | Paper | |||
| Removing raindrops from a single image using synthetic data |
2020 | π· | Paper | |||
| A2Net: Adjacent Aggregation Networks for Image Raindrop Removal |
2020 | π· | Paper | |||
| Detection and removal of rain from videos |
2004 | πΉ | Paper | |||
| A survey of single image rain removal based on deep learning |
2023 | π· | Paper | |||
| Single-image raindrop removal using concurrent channel-spatial attention and long-short skip connections |
2020 | π· | Paper | |||
| Rain drop detection and removal using k-means clustering |
2015 | π· | Paper | |||
| Improved sea-ice identification using semantic segmentation with raindrop removal |
2022 | π· | Paper | |||
| All in one bad weather removal using architectural search |
2020 | π· | Paper | |||
| Detection and removal of raindrop from images using deeplearning |
2019 | π· | Paper | |||
| Raindrop Removal for In-Vehicle Camera Images with Generative Adversarial Network |
2022 | π· | Paper | |||
| Iterative contrastive learning for single image raindrop removal |
2022 | π· | Paper | |||
| Removal of rain from videos: a review |
2014 | πΉ | Paper | |||
| Image raindrop removal method for generative adversarial network based on difference learning |
2020 | π· | Paper | |||
| Single Image Raindrop Removal Using a Non-Local Operator and Feature Maps in the Frequency Domain |
2022 | π· | Paper | |||
| Deep learning for seeing through window with raindrops |
2019 | π· | Paper | |||
| Raindrop Removal using Image Inpainting |
2023 | π· | Paper | |||
| Mutual channel prior guided dual-domain interaction network for single image raindrop removal |
2023 | π· | Paper | |||
| Recovering raindrop removal images under heavy rain. |
2020 | π· | Paper | |||
| X-net for single image raindrop removal |
2020 | π· | Paper | |||
| Removing rain and snow in a single image using guided filter |
2012 | π· | Paper | |||
| Not All Areas Are Equal: A Novel SeparationβRestorationβFusion Network for Image Raindrop Removal |
2020 | π· | Paper | |||
| RIADNet: single image deraining network for raindrops and rain streaks removal |
2025 | π· | Paper | |||
| An Image Raindrop Removal Method Based on Squeeze-Excitation and Residual Fusion |
2024 | π· | Paper | |||
| A dual CNN architecture for single image raindrop and rain streak removal |
2022 | π· | Paper | |||
| Raindropβimpactβinduced erosion processes and prediction: a review |
2005 | π· | Paper | |||
| Cycle-spinning gan for raindrop removal from images |
2019 | π· | Paper | |||
| Application research on improved CGAN in image raindrop removal |
2019 | π· | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Data | Method | Link | Code |
|---|---|---|---|---|---|---|
| All snow removed: Single image desnowing algorithm using hierarchical dual-tree complex wavelet representation and contradict channel loss |
2021 | π· | Paper | |||
| Smartassign: Learning a smart knowledge assignment strategy for deraining and desnowing |
2023 | π· | Paper | |||
| Video desnowing and deraining based on matrix decomposition |
2017 | πΉ | Paper | |||
| A scalable and accurate de-snowing algorithm for LiDAR point clouds in winter |
2022 | π· | Paper | |||
| Hcsd-net: Single image desnowing with color space transformation |
2023 | π· | Paper | |||
| Image desnowing via deep invertible separation |
2023 | π· | Paper | |||
| Towards efficient single image dehazing and desnowing |
2204 | π· | Paper | |||
| Deep unfolding network for image desnowing with snow shape prior |
2025 | π· | Paper | |||
| Enabling renewable energy technologies in harsh climates with ultraβefficient electroβthermal desnowing, defrosting, and deicing |
2022 | π· | Paper | |||
| Semi-supervised video desnowing network via temporal decoupling experts and distribution-driven contrastive regularization |
2024 | πΉ | Paper | |||
| SnowFormer: Context interaction transformer with scale-awareness for single image desnowing |
2208 | π· | Paper | |||
| Video deraining and desnowing using temporal correlation and low-rank matrix completion |
2015 | πΉ | Paper | |||
| Enhancing outdoor vision: Binocular desnowing with dual-stream temporal transformer |
2026 | π· | Paper | |||
| De-snowing LiDAR point clouds with intensity and spatial-temporal features |
2022 | π· | Paper | |||
| De-snowing algorithm for long-wavelength LiDAR |
2024 | π· | Paper | |||
| Fast and accurate desnowing algorithm for LiDAR point clouds |
2020 | π· | Paper | |||
| LiDAR De-Snow Score (DSS): combining quality and perception metrics for optimised de-noising |
2025 | π· | Paper | |||
| Towards real-time high-definition image snow removal: Efficient pyramid network with asymmetrical encoder-decoder architecture |
2022 | π· | Paper | |||
| Dual gradient based snow attentive desnowing |
2023 | π· | Paper | |||
| An efficient video desnowing and deraining method with a novel variant dataset |
2021 | πΉ | Paper | |||
| Simultaneous snow mask prediction and single image desnowing with a bidirectional attention transformer network |
2024 | π· | Paper | |||
| LiDAR de-snowing method with density and intensity fusion |
2023 | π· | Paper | |||
| An integrated multi-scale context-aware network for efficient desnowing |
2025 | π· | Paper | |||
| Event-Based De-Snowing for Autonomous Driving |
2025 | π· | Paper | |||
| Video Desnower: An Adaptive Feature Fusion Understanding Video Desnowing Model With Deformable Convolution and KNN Point Cloud Transformer |
2024 | πΉ | Paper | |||
| Msp-former: Multi-scale projection transformer for single image desnowing |
2023 | π· | Paper | |||
| Lightweight image de-snowing: A better trade-off between network capacity and performance |
2023 | π· | Paper | |||
| SnowMaster: Comprehensive Real-world Image Desnowing via MLLM with Multi-Model Feedback Optimization |
2025 | π· | Paper | |||
| Optimized connections and feature interactions for more efficient single-image desnowing |
2025 | π· | Paper | |||
| Context-aware coarse-to-fine network for single image desnowing |
2024 | π· | Paper | |||
| Two-Stage Nighttime Desnowing Diffusion Model Based on Pseudo-Scenario Reconstruction |
2024 | π· | Paper | |||
| Video desnowing and deraining via saliency and dual adaptive spatiotemporal filtering |
2021 | πΉ | Paper | |||
| Uncertainty-driven dynamic degradation perceiving and background modeling for efficient single image desnowing |
2023 | π· | Paper | |||
| Exploring Local Sparse Structure Prior for Image Deraining and Desnowing |
2024 | π· | Paper | |||
| RVDNet: a two-stage network for real-world video desnowing with domain adaptation |
2024 | πΉ | Paper | |||
| Slide: Self-supervised lidar de-snowing through reconstruction difficulty |
2022 | π· | Paper | |||
| FedDeSnowNet: Federated De-snowing Network for LiDAR Point Clouds |
2024 | π· | Paper | |||
| Image snow removal methods for robotic environment fusion |
2019 | π· | Paper | |||
| Stacked dense networks for single-image snow removal |
2019 | π· | Paper | |||
| LIDAR De-Snow Score (DSS): combining quality and perception metrics for optimised data filtering |
2024 | π· | Paper | |||
| Wavelet-Enhanced Desnowing: A Novel Single Image Restoration Approach for Traffic Surveillance under Adverse Weather Conditions |
2503 | π· | Paper | |||
| Unsupervised Domain Adaptive Learning for Image Desnowing with Real-World Data |
2023 | π· | Paper | |||
| Snow removal in video: A new dataset and a novel method |
2023 | πΉ | Paper | |||
| Deep dense multi-scale network for snow removal using semantic and depth priors |
2021 | π· | Paper | |||
| Deraining and Desnowing Algorithm on Adaptive Tolerance and Dual-tree Complex Wavelet Fusion |
2020 | π· | Paper | |||
| Feature Fusion Attention Network with CycleGAN for Image Dehazing, De-Snowing and De-Raining |
2503 | π· | Paper | |||
| Stereo video deraining and desnowing based on spatiotemporal frame warping |
2014 | πΉ | Paper | |||
| Desnowformer: an effective transformer-based image desnowing network |
2022 | π· | Paper | |||
| Star-Net: Improving Single Image Desnowing Model With More Efficient Connection and Diverse Feature Interaction |
2303 | π· | Paper | |||
| Check for updates Lidar De-snowing Method with Density and Intensity Fusion |
2023 | π· | Paper | |||
| Singleβimage snow removal algorithm based on generative adversarial networks |
2023 | π· | Paper | |||
| Degradation-adaptive neural network for jointly single image dehazing and desnowing |
2024 | π· | Paper | |||
| Thermal characterisation of electroconductive layers for anti-icing and de-snowing applications on roads |
2022 | π· | Paper | |||
| Snowed autoencoders are efficient snow removers |
2023 | π· | Paper | |||
| Rain and Snow Removal |
2021 | π· | Paper | |||
| Single image rain/snow removal using distortion type information |
2022 | π· | Paper | |||
| SnowSTNet: A Spatial-Temporal LiDAR Point Cloud Denoising Network for Autonomous Driving in Snowy Weather |
2025 | π· | Paper | |||
| Denoising framework based on multiframe continuous point clouds for autonomous driving LiDAR in snowy weather |
2024 | π· | Paper | |||
| Cross-Stitched Multi-task Dual Recursive Networks for Unified Single Image Deraining and Desnowing |
2022 | π· | Paper | |||
| Adaptive two-stage filter for de-snowing LiDAR point clouds |
2022 | π· | Paper | |||
| Ultra-efficient and ultra-rapid solar cell de-icing and de-snowing |
2021 | π· | Paper | |||
| Single Image Desnow Based on Vision Transformer and Conditional Generative Adversarial Network for Internet of Vehicles. |
2023 | π· | Paper | |||
| Weatherstream: Light transport automation of single image deweathering |
2023 | π· | Paper | |||
| Parameter-efficient fine-tuning for single image snow removal |
2025 | π· | Paper | |||
| Snow removal for LiDAR point clouds with spatio-temporal conditional random fields |
2023 | π· | Paper | |||
| Desnow-Gnn: Spatiotemporal Graph Neural Network for Robust Lidar Point Cloud Denoising in Adverse Weather |
5364 | π· | Paper | |||
| SnowMamba: Achieving More Precise Snow Removal with Mamba |
2025 | π· | Paper | |||
| Video Desnowing Algorithm Based on Multi-Channel Fusion and Group Sparse Coding |
2023 | πΉ | Paper | |||
| Beyond the snowfall: Enhancing snowy day object detection through progressive restoration and multi-feature fusion |
2024 | π· | Paper | |||
| A simulation computation of twist of De-Snowing electric wires due to snow accretion |
1976 | π· | Paper | |||
| Restoring snow-degraded single images with wavelet in vision transformer |
2023 | π· | Paper | |||
| SnowTextNet: Detection-Guided Restoration Dual-Branch Network for Text Detection in Snowy Scenes |
2025 | π· | Paper | |||
| How Hard Is Snow? A Paired Domain Adaptation Dataset for Clear and Snowy Weather: CADC+ |
2025 | π· | Paper | |||
| Restoring vision in adverse weather conditions with patch-based denoising diffusion models |
2023 | π· | Paper | |||
| Simulating Marine Snow Images: Pipeline, Data Set, and Benchmark |
2025 | π· | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Data | Method | Link | Code |
|---|---|---|---|---|---|---|
| All in One Bad Weather Removal Using Architectural Search Ruoteng Li, Robby T. Tan, Loong-Fah Cheong |
CVPR | 2020 | π· | Paper | ||
| Interactive (de) weathering of an image using physical models |
2003 | π· | Paper | |||
| Weatherstream: Light transport automation of single image deweathering |
2023 | π· | Paper | |||
| Learning real-world image de-weathering with imperfect supervision |
2024 | π· | Paper | |||
| Residual deformable convolution for better image de-weathering |
2024 | π· | Paper | |||
| Automatic image de-weathering using physical model and maximum entropy |
2008 | π· | Paper | |||
| Review on state of art image enhancement and restoration methods for a vision based driver assistance system with De-weathering |
2011 | π· | Paper | |||
| Pseudo-Label Guided Real-World Image De-weathering: A Learning Framework with Imperfect Supervision |
2025 | π· | Paper | |||
| Highlights on weathering effects: Improving the appearance modeling of weathering effects on images |
2010 | π· | Paper | |||
| Fast single image and video deweathering using look-up-table approach |
2015 | πΉ | Paper | |||
| Automatic image de-weathering using curvelet-based vanishing point detection |
2007 | π· | Paper | |||
| Image de-weathering for road based on physical model |
2009 | π· | Paper | |||
| Gpu-accelerated real-time surveillance de-weathering |
2013 | π· | Paper | |||
| Real time image and video deweathering: The future prospects and possibilities |
2016 | πΉ | Paper | |||
| Identifying decadal trends in deweathered concentrations of criteria air pollutants in Canadian urban atmospheres with machine learning approaches |
2024 | π· | Paper | |||
| A hybrid approach for a vision based driver assistance system with de-weathering |
2012 | π· | Paper | |||
| Machine learning 'De-Weathering 'of urban NOx data to quantify meteorological impacts at two traffic sites in Germany |
2020 | π· | Paper | |||
| Meteorological Normalization or Deweathering for Predicting Air Pollutant Concentration: Pitfalls and Limitations |
2024 | π· | Paper | |||
| Spatial, temporal features and influence of meteorology on PM2. 5 and O3 association across urban and rural environments of India |
2024 | π· | Paper | |||
| Significant changes in chemistry of fine particles in wintertime Beijing from 2007 to 2017: impact of clean air actions |
2019 | π· | Paper | |||
| Identifying decadal trends in deweathered concentrations of criteria air pollutants in Canadian urban atmospheres with machine learning approaches |
2023 | π· | Paper | |||
| A Review on Deweathering Methods: Fog & Haze Removal |
2016 | π· | Paper | |||
| Impacts of emergency health protection measures upon air quality, traffic and public health: evidence from Oxford, UK |
2022 | π· | Paper | |||
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2023 | π· | Paper | |||
| Deep learning-based weather image recognition |
2018 | π· | Paper | |||
| Evaluating the real changes of air quality due to clean air actions using a machine learning technique: Results from 12 Chinese mega-cities during 2013β2020 |
2022 | π· | Paper | |||
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2021 | π· | Paper | |||
| Does COVID-19 lockdown matter for air pollution in the short and long run in China? A machine learning approach to policy evaluation |
2024 | π· | Paper | |||
| The impact of urban mobility on air pollution in Kampala, an exemplar sub-Saharan African city |
2024 | π· | Paper | |||
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2023 | π· | Paper | |||
| Space weathering (and de-weathering) of asteroids. |
2014 | π· | Paper | |||
| Quantifying the impact of clean air policy interventions for air quality management |
2022 | π· | Paper | |||
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2023 | π· | Paper | |||
| Decadal Trends of Criteria Pollutants and PM2. 5 Components in Canadian Cities |
2022 | π· | Paper | |||
| Investigating the impact of meteorology and emissions on PM2.5 and PM10 in Delhi using machine learning |
2025 | π· | Paper | |||
| Adverse weather removal with codebook priors |
2023 | π· | Paper | |||
| Language-driven all-in-one adverse weather removal |
2024 | π· | Paper | |||
| Learning multiple adverse weather removal via two-stage knowledge learning and multi-contrastive regularization: Toward a unified model |
2022 | π· | Paper | |||
| Exploring the application of large-scale pre-trained models on adverse weather removal |
2024 | π· | Paper | |||
| Mowe: mixture of weather experts for multiple adverse weather removal |
2023 | π· | Paper | |||
| Learning weather-general and weather-specific features for image restoration under multiple adverse weather conditions |
2023 | π· | Paper | |||
| Transweather: Transformer-based restoration of images degraded by adverse weather conditions |
2022 | π· | Paper | |||
| Continuous adverse weather removal via degradation-aware distillation |
2025 | π· | Paper | |||
| DRR: A new method for multiple adverse weather removal |
2025 | π· | Paper | |||
| Image all-in-one adverse weather removal via dynamic model weights generation |
2024 | π· | Paper | |||
| Always clear days: Degradation type and severity aware all-in-one adverse weather removal |
2025 | π· | Paper | |||
| Continual all-in-one adverse weather removal with knowledge replay on a unified network structure |
2024 | π· | Paper | |||
| CMAWRNet: Multiple Adverse Weather Removal via a Unified Quaternion Neural Architecture |
2505 | π· | Paper | |||
| Genuine knowledge from practice: Diffusion test-time adaptation for video adverse weather removal |
2024 | πΉ | Paper | |||
| Rethinking all-in-one adverse weather removal for object detection |
2024 | π· | Paper | |||
| SemiDDM-Weather: A Semi-supervised Learning Framework for All-in-one Adverse Weather Removal |
2024 | π· | Paper | |||
| Framework for generation and removal of multiple types of adverse weather from driving scene images |
2023 | π· | Paper | |||
| Robust Adverse Weather Removal via Spectral-based Spatial Grouping |
2507 | π· | Paper | |||
| Multimodal prompt state space models for unified adverse weather removal |
2025 | π· | Paper | |||
| Multiple Adverse Weather Removal Using Masked-Based Pre-Training and Dual-Pooling Adaptive Convolution |
2024 | π· | Paper | |||
| Video adverse-weather-component suppression network via weather messenger and adversarial backpropagation |
2023 | πΉ | Paper | |||
| All in one bad weather removal using architectural search |
2020 | π· | Paper | |||
| Decoupling degradation and content processing for adverse weather image restoration |
2023 | π· | Paper | |||
| WM-MoE: Weather-aware multi-scale mixture-of-experts for blind adverse weather removal |
2023 | π· | Paper | |||
| Prompt to Restore, Restore to Prompt: Cyclic Prompting for Universal Adverse Weather Removal |
2025 | π· | Paper | |||
| All-in-one adverse weather removal via dual state space-based diffusion model with degradation-aware guidance |
2026 | π· | Paper | |||
| RestoreCUFormer: Transformers to Make Strong Encoders via Two-stage Knowledge Learning For Multiple Adverse Weather Removal |
2024 | π· | Paper | |||
| Learning to remove bad weather: towards robust visual perception for self-driving |
2022 | π· | Paper | |||
| Restoring images in adverse weather conditions via histogram transformer |
2024 | π· | Paper | |||
| Removing Multiple Hybrid Adverse Weather in Video via a Unified Model |
2025 | πΉ | Paper | |||
| WeatherClean: An Image Restoration Algorithm for UAV-Based Railway Inspection in Adverse Weather |
2025 | π· | Paper | |||
| Low-rank adaptation-based all-weather removal for autonomous navigation |
2411 | π· | Paper | |||
| TAP: Parameter-efficient Task-Aware Prompting for Adverse Weather Removal |
2025 | π· | Paper | |||
| Point cloud processing under adverse weather: a survey of datasets, enhancement, and denoising methods |
2025 | π· | Paper | |||
| DDCNet: Advanced Decoupling of Degradation and Content for Adverse Weather Image Restoration |
2025 | π· | Paper | |||
| Multiple adverse weather removal using adversarial and contrastive learning |
2023 | π· | Paper | |||
| ART-SS: an adaptive rejection technique for semi-supervised restoration for adverse weather-affected images |
2022 | π· | Paper | |||
| Restoring vision in adverse weather conditions with patch-based denoising diffusion models |
2023 | π· | Paper | |||
| 4denoisenet: Adverse weather denoising from adjacent point clouds |
2022 | π· | Paper | |||
| Combating bad weather part i: Rain removal from video |
2014 | πΉ | Paper | |||
| Allweather-net: Unified image enhancement for autonomous driving under adverse weather and low-light conditions |
2024 | π· | Paper | |||
| A Review of Unmanned Visual Target Detection in Adverse Weather |
2025 | π· | Paper | |||
| Disentangled bad weather removal gan for pedestrian detection |
2022 | π· | Paper | |||
| Learning to Restore Arbitrary Hybrid adverse weather Conditions in one go |
2025 | π· | Paper | |||
| Analysis of adverse weather for excusable delays |
2010 | π· | Paper | |||
| Current and future approaches to wet weather flow management: A review |
2021 | π· | Paper | |||
| Towards real-world adverse weather image restoration: Enhancing clearness and semantics with vision-language models |
2024 | π· | Paper | |||
| Multi-weather city: Adverse weather stacking for autonomous driving |
2021 | π· | Paper | |||
| Weathergs: 3d scene reconstruction in adverse weather conditions via gaussian splatting |
2412 | π· | Paper | |||
| Study of Filtering the Weather Adverse Effects to Object Detection |
2024 | π· | Paper | |||
| Learning with confidence the likelihood of flight diversion due to adverse weather at destination |
2023 | π· | Paper | |||
| β¦ Encoder and Decoder-Based Transformer Fusion with Deep Residual Attention for Restoration of Degraded Images and Clear Visualization in Adverse Weather β¦ |
2024 | π· | Paper | |||
| Cfmw: Cross-modality fusion mamba for multispectral object detection under adverse weather conditions |
2404 | π· | Paper | |||
| Framework of degraded image restoration and simultaneous localization and mapping for multiple bad weather conditions |
2023 | π· | Paper | |||
| Problems related to the operation of autonomous vehicles in adverse weather conditions |
2023 | π· | Paper | |||
| TANet: Triplet attention network for all-in-one adverse weather image restoration |
2024 | π· | Paper | |||
| Power Line Aerial Image Restoration Under Adverse Weather: Datasets and Baselines |
2025 | π· | Paper | |||
| Unified multi-weather visibility restoration |
2022 | π· | Paper | |||
| Degradation type-aware image restoration for effective object detection in adverse weather |
2024 | π· | Paper | |||
| Da-raw: Domain adaptive object detection for real-world adverse weather conditions |
2024 | π· | Paper | |||
| Cnn-based lidar point cloud de-noising in adverse weather |
2020 | π· | Paper | |||
| Let it snow: On the synthesis of adverse weather image data |
2021 | π· | Paper | |||
| DS-Diff: a dual-stage network with degradation-aware and semantic-aware for adverse weather removal based on diffusion models |
2025 | π· | Paper | |||
| AdverseNet: A Unified LiDAR Point Cloud Denoising Network for Autonomous Driving in Adverse Weather |
2025 | π· | Paper | |||
| Contrast restoration of weather degraded images |
2003 | π· | Paper | |||
| Teaching tailored to talent: Adverse weather restoration via prompt pool and depth-anything constraint |
2024 | π· | Paper | |||
| Enhancing robustness of weather removal: preprocessing-based defense against adversarial attacks |
2024 | π· | Paper | |||
| Role of adverse weather in key crash types on limited-access: roadways implications for advanced weather systems |
1998 | π· | Paper | |||
| Survey on lidar perception in adverse weather conditions |
2023 | π· | Paper | |||
| Gridformer: Residual dense transformer with grid structure for image restoration in adverse weather conditions |
2024 | π· | Paper | |||
| Vehicle detection and tracking in adverse weather using a deep learning framework |
2020 | π· | Paper | |||
| Rethinking LiDAR object detection in adverse weather conditions |
2022 | π· | Paper | |||
| Visual quality enhancement of images under adverse weather conditions |
2018 | π· | Paper | |||
| Worsening perception: Real-time degradation of autonomous vehicle perception performance for simulation of adverse weather conditions |
2021 | π· | Paper | |||
| Depth-aware blind image decomposition for real-world adverse weather recovery |
2024 | π· | Paper | |||
| Robust object detection in challenging weather conditions |
2024 | π· | Paper | |||
| Gradient-Guided Parameter Mask for Multi-Scenario Image Restoration Under Adverse Weather |
2411 | π· | Paper | |||
| Wavelet-Enhanced Desnowing: A Novel Single Image Restoration Approach for Traffic Surveillance under Adverse Weather Conditions |
2503 | π· | Paper | |||
| IDP-YOLOV9: Improvement of Object Detection Model in Severe Weather Scenarios from Drone Perspective. |
2076 | π· | Paper | |||
| Object Detection in Adverse Weather Conditions using Machine Learning |
2023 | π· | Paper | |||
| Weather removal with a lightweight quaternion Chebyshev neural network |
2023 | π· | Paper | |||
| Q-KAN: enhancing robustness of weather removal: preprocessing-based defense against adversarial attacks |
2025 | π· | Paper | |||
| MODEM: A Morton-Order Degradation Estimation Mechanism for Adverse Weather Image Recovery |
2505 | π· | Paper | |||
| Perception methods for adverse weather based on vehicle infrastructure cooperation system: A review |
2024 | π· | Paper | |||
| ARODNet: adaptive rain image enhancement object detection network for autonomous driving in adverse weather conditions |
2023 | π· | Paper | |||
| AWRaCLe: All-weather image restoration using visual in-context learning |
2025 | π· | Paper | |||
| Dsor: A scalable statistical filter for removing falling snow from lidar point clouds in severe winter weather |
2109 | π· | Paper | |||
| The impact of adverse weather conditions on autonomous vehicles: How rain, snow, fog, and hail affect the performance of a self-driving car |
2019 | π· | Paper | |||
| Prompt-guided and degradation prior supervised transformer for adverse weather image restoration |
2025 | π· | Paper | |||
| Adverse weather target detection algorithm based on adaptive color levels and improved YOLOv5 |
2022 | π· | Paper | |||
| Test-time Adaptation for Real-World Video Adverse Weather Restoration with Meta Batch Normalization |
2025 | πΉ | Paper | |||
| Restoring images captured in arbitrary hybrid adverse weather conditions in one go |
2023 | π· | Paper | |||
| Unifying Physically-Informed Weather Priors in A Single Model for Image Restoration Across Multiple Adverse Weather Conditions |
2025 | π· | Paper | |||
| Perception-friendly video enhancement for autonomous driving under adverse weather conditions |
2022 | πΉ | Paper | |||
| A decision support method for flight cancellations in adverse weather: An airport perspective |
2015 | π· | Paper | |||
| AdWeatherNet: Adverse Weather Denoising with Point Cloud Spatiotemporal Attention |
2024 | π· | Paper | |||
| Adaptive enhancement of spatial information in adverse weather |
2024 | π· | Paper | |||
| WRRT-DETR: weather-robust RT-DETR for drone-view object detection in adverse weather |
2025 | π· | Paper | |||
| Rethinking data augmentation for robust lidar semantic segmentation in adverse weather |
2024 | π· | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|---|---|---|---|---|---|
| Three-Channel Infrared Imaging for Object Detection in Haze Beinan Yu, Yifan Chen, Si-Yuan Cao, Hui-Liang Shen, Junwei Li |
TIM | 2022 | Haze | π· | Paper | |
| Detection-Friendly Dehazing: Object Detection in Real-World Hazy Scenes Chengyang Li; Heng Zhou; Yang Liu; Caidong Yang; Yongqiang Xie; Zhongbo Li |
TPAMI | 2023 | Haze | π· | Paper | |
| Unified Density-Aware Image Dehazing and Object Detection in Real-World Hazy Scenes Zhengxi Zhangβ, Liang Zhaoβ, Yunan Liu, Shanshan Zhang, Jian Yan |
ACCV | 2020 | Haze | π· | Paper | Code |
| HazyDet: Open-Source Benchmark for Drone-View Object Detection with Depth-Cues in Hazy Scenes Changfeng Feng, Zhenyuan Chen, Xiang Li, Chunping Wang, Jian Yang, Ming-Ming Cheng, Yimian Dai, Qiang Fu |
ArXiv | 2024 | Haze | π· π | Paper | Code |
| Rain Rendering for Evaluating and Improving Robustness to Bad Weather Maxime Tremblay, Shirsendu Sukanta Halder, Raoul de Charette & Jean-FranΓ§ois Lalonde |
IJCV | 2020 | π§οΈ | π· | Paper | Code |
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|---|---|---|---|---|---|
| Rain Rendering for Evaluating and Improving Robustness to Bad Weather Maxime Tremblay, Shirsendu Sukanta Halder, Raoul de Charette & Jean-FranΓ§ois Lalonde |
IJCV | 2020 | π§οΈ | π· | Paper | Code |
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|---|---|---|---|---|---|
| DEHRFormer: Real-Time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes Sixiang Chen; Tian Ye; Jun Shi; Yun Liu; JingXia Jiang; Erkang Chen |
ICASSP | 2023 | π«οΈ | π· | Paper | |
| Depth Estimation for Hazy Images Using Deep Learning Laksmita Rahadianti; Fumihiko Sakaue; Jun Sato |
ACPR | 2017 | π«οΈ | π· | Paper | |
| CNN-Based Simultaneous Dehazing and Depth Estimation Byeong-Uk Lee; Kyunghyun Lee; Jean Oh; In So Kweon |
ICRA | 2020 | π«οΈ | π· | Paper | |
| S2DNet: Depth Estimation From Single Image and Sparse Samples Praful Hambarde; Subrahmanyam Murala |
TCI | 2020 | π«οΈ | π· | Paper | |
| Depth-Centric Dehazing and Depth-Estimation from Real-World Hazy Driving Video Junkai Fan, Kun Wang, Zhiqiang Yan, Xiang Chen, Shangbing Gao, Jun Li, Jian Yang |
AAAI | 2025 | π«οΈ | πΉ | Paper | Code |
| Combining semantic scene priors and haze removal for single image depth estimation Ke Wang; Enrique Dunn; Joseph Tighe; Jan-Michael Frahm |
WACV | 2014 | π«οΈ | π· | Paper | |
| Depth Estimation from Single Hazy Images with 2-Phase Training Laksmita Rahadianti; Fumihiko Sakaue; Jun Sato |
ICACSIS | 2020 | π«οΈ | π· | Paper | |
| Progressive dehazing and depth estimation from a single hazy image Jeonghoon Kim, Sungyoon Kim, Changhoon Pyo, Hyeongmyeon Kim, Changhoon Yi |
IEIE SPC | 2022 | π«οΈ | π· | Paper | |
| Image-Based PM2.5 Estimation and its Application on Depth Estimation Jian Ma; Kun Li; Yahong Han; Pufeng Du; Jingyu Yang |
ICASSP | 2018 | π«οΈ | π· | Paper | |
| S2DNet: Depth Estimation From Single Image and Sparse Samples Praful Hambarde; Subrahmanyam Murala |
TCI | 2020 | π«οΈ | π· | Paper | |
| Robust Depth Estimation in Foggy Environments Combining RGB Images and mmWave Radar Mengchen Xiong; Xiao Xu; Dong Yang; Eckehard Steinbach |
ISM | 2022 | π«οΈ | π· | Paper | |
| FoggyDepth: Leveraging Channel Frequency and Non-Local Features for Depth Estimation in Fog Mengjiao Shen; Liuyi Wang; Xianyou Zhong; Chengju Liu; Qijun Chen |
TCSVT | 2025 | π«οΈ | π· | Paper | |
| Fog density estimation and image defogging based on surrogate modeling for optical depth Yutong Jiang; Changming Sun; Yu Zhao; Li Yang |
TIP | 2017 | π«οΈ | π· | Paper | |
| Example based depth from fog Kristofor B. Gibson; Serge J. Belongie; Truong Q. Nguyen |
ICIP | 2013 | π«οΈ | π· | Paper | |
| An enhanced window-variant dark channel prior for depth estimation using single foggy image Jie Chen; Lap-Pui Chau |
ICIP | 2013 | π«οΈ | π· | Paper | |
| Self-supervised monocular depth estimation in fog Bo Taoβ , Jiaxin Huβ , Du Jiang, Gongfa Li, Baojia Chen, Xinbo Qian |
OE | 2022 | π«οΈ | π· | Paper | Code |
| Estimating Fog Parameters From an Image Sequence Using Non-Linear Optimisation Yining Ding, Andrew M. Wallace, Sen Wang |
WACV | 2024 | π«οΈ | π· | Paper | |
| Factorizing Scene Albedo and Depth from a Single Foggy Image Louis Kratz; Ko Nishino |
ICCV | 2009 | π«οΈ | π· | Paper | |
| Self-supervised Monocular Depth Estimation: Let's Talk About The Weather Kieran Saunders, George Vogiatzis, Luis J. Manso |
ICCV | 2023 | π«οΈπ§οΈβοΈ | π· | Paper | Code |
| Unsupervised Monocular Depth Estimation for Foggy Images with Domain Separation and Self-Depth Domain Conversion Fuyang Liu, Jianjun Li |
CVM | 2025 | π«οΈ | π· | Paper | |
| Depth from phasor distortions in fog Takeshi Muraji, Kenichiro Tanaka, Takuya Funatomi, Yasuhiro Mukaigawa |
Optics Express | 2019 | π«οΈ | π· | Paper | Code |
| Gated2Gated: Self-Supervised Depth Estimation from Gated Images Amanpreet Walia, Stefanie Walz, Mario Bijelic, Fahim Mannan, Frank Julca-Aguilar, Michael Langer, Werner Ritter, Felix Heide |
CVPR | 2022 | π«οΈβοΈ | π· | Paper | Code |
| Paper | Code | |||||
| Rain Rendering for Evaluating and Improving Robustness to Bad Weather Maxime Tremblay, Shirsendu Sukanta Halder, Raoul de Charette & Jean-FranΓ§ois Lalonde |
IJCV | 2020 | π§οΈ | π· | Paper | Code |
| Robust Monocular Depth Estimation under Challenging Conditions Stefano Gasperini, Nils Morbitzer, HyunJun Jung, Nassir Navab, Federico Tombari |
ICCV | 2023 | π§οΈπ | π· | Paper | Code |
| Empirical Study: Monocular Depth Estimation from RGB, NIR, Thermal Image in Adverse Weather Conditions Ukcheol Shin; Soonmin Hwang; Jean Oh |
ICTC | 2023 | π§οΈβοΈπ | Paper |
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|
Paper List (click to expand)
| Paper | Venue | Year | Weather | Data | Link | Code |
|---|---|---|---|---|---|---|
| Dehazing-NeRF: Neural Radiance Fields from Hazy Images Tian Li, LU Li, Wei Wang, Zhangchi Feng |
Arxiv | 2023 | π«οΈ | π· | Paper | Code |
| DehazeNeRF: Multiple Image Haze Removal and 3D Shape Reconstruction using Neural Radiance Fields Wei-Ting Chen, Wang Yifan, Sy-Yen Kuo, Gordon Wetzstein |
3DV | 2024 | π«οΈ | π· | Paper | Code |
| RainyScape: Unsupervised Rainy Scene Reconstruction using Decoupled Neural Rendering Xianqiang Lyu, Hui Liu, Junhui Hou |
MM | 2024 | π§οΈ | π· | Paper | Code |
| DeRainGS: Gaussian Splatting for Enhanced Scene Reconstruction in Rainy Environments Shuhong Liu, Xiang Chen, Hongming Chen, Quanfeng Xu, Mingrui Li |
AAAI | 2025 | π§οΈ | π· | Paper | |
| DerainNeRF: 3D Scene Estimation with Adhesive Waterdrop Removal Yunhao Li, Jing Wu, Lingzhe Zhao, Peidong Liu |
ICRA | 2024 | π§ | π· | Paper | Code |
| Weathergs: 3d scene reconstruction in adverse weather conditions via gaussian splatting Chenghao Qian, Yuhu Guo, Wenjing Li, Gustav Markkula |
ICRA | 2025 | π§οΈβοΈ | π· | Paper | Code |
| ClimateNeRF: Extreme Weather Synthesis in Neural Radiance Field Yuan Li, Zhi-Hao Lin, David Forsyth, Jia-Bin Huang, Shenlong Wang |
ICCV | 2023 | π«οΈβοΈ | π· | Paper | Code |
| Rain Rendering for Evaluating and Improving Robustness to Bad Weather Maxime Tremblay, Shirsendu Sukanta Halder, Raoul de Charette & Jean-FranΓ§ois Lalonde |
IJCV | 2020 | π§οΈ | π· | Paper | Code |
| WeatherDiffusion: Weather-Guided Diffusion Model for Forward and Inverse Rendering Yixin Zhu, Zuoliang Zhu, MiloΕ‘ HaΕ‘an, Jian Yang, Jin Xie, Beibei Wang |
Arxiv | 2025 | π«οΈπ§οΈβοΈ | π· | Paper | |
| Physics-Based Rendering for Improving Robustness to Rain Shirsendu Halder; Jean-Francois Lalonde; Raoul De Charette |
ICCV | 2019 | π§οΈ | π· | Paper | Code |
| ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Rendering Andrea Ramazzina, Mario Bijelic, Stefanie Walz, Alessandro Sanvito, Dominik Scheuble, Felix Heide |
ICCV | 2023 | π«οΈ | π· | Paper | Code |
| ClimateGS: Real-Time Climate Simulation with 3D Gaussian Style Transfer Yuezhen Xie, Meiying Zhang, Qi Hao |
Arxiv | 2025 | :snow: | π· | Paper | |
| WeatherEdit: Controllable Weather Editing with 4D Gaussian Field Chenghao Qian, Wenjing Li, Yuhu Guo, Gustav Markkula |
Arxiv | 2025 | π«οΈπ§οΈβοΈ | π· | Paper | Code |
D-hazy: A dataset to evaluate quantitatively dehazing algorithms