# Robust Representation Learning with Feedback for Single Image Deraining

arXiv: https://arxiv.org/abs/2101.12463 · HTML: https://mlsanity.com/paper/2101.12463/

## Key facts

- Cited by 32 papers in the map (data through 14 Oct 2026).
- Builds on 21 of its 38 references that are in the map.
- First posted on arXiv 29 Jan 2021.

## Builds on (most cited first, 21 of 21)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation](https://mlsanity.com/paper/1802.02611/) (2018)
- [What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?](https://mlsanity.com/paper/1703.04977/) (2017)
- [Group Normalization](https://mlsanity.com/paper/1803.08494/) (2018)
- [Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics](https://mlsanity.com/paper/1705.07115/) (2017)
- [Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition](https://mlsanity.com/paper/1406.4729/) (2014)
- [Deep Joint Rain Detection and Removal from a Single Image](https://mlsanity.com/paper/1609.07769/) (2016)
- [Progressive Image Deraining Networks: A Better and Simpler Baseline](https://mlsanity.com/paper/1901.09221/) (2019)
- [Multi-Scale Progressive Fusion Network for Single Image Deraining](https://mlsanity.com/paper/2003.10985/) (2020)
- [Density-aware Single Image De-raining using a Multi-stream Dense Network](https://mlsanity.com/paper/1802.07412/) (2018)
- [Understanding image representations by measuring their equivariance and equivalence](https://mlsanity.com/paper/1411.5908/) (2014)
- [Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining](https://mlsanity.com/paper/1807.05698/) (2018)
- [Attentive Generative Adversarial Network for Raindrop Removal from a Single Image](https://mlsanity.com/paper/1711.10098/) (2017)
- [Image De-raining Using a Conditional Generative Adversarial Network](https://mlsanity.com/paper/1701.05957/) (2017)
- [Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset](https://mlsanity.com/paper/1904.01538/) (2019)
- [Clearing the Skies: A deep network architecture for single-image rain removal](https://mlsanity.com/paper/1609.02087/) (2016)
- [A Model-driven Deep Neural Network for Single Image Rain Removal](https://mlsanity.com/paper/2005.01333/) (2020)
- [Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining](https://mlsanity.com/paper/1906.11129/) (2019)
- [Decoupled Learning for Conditional Adversarial Networks](https://mlsanity.com/paper/1801.06790/) (2018)
- [A Coarse-to-Fine Multi-stream Hybrid Deraining Network for Single Image Deraining](https://mlsanity.com/paper/1908.10521/) (2019)

## Built on by (most cited first, 30 of 32)

- [Unpaired Deep Image Deraining Using Dual Contrastive Learning](https://mlsanity.com/paper/2109.02973/) (2021)
- [Degradation-Aware Feature Perturbation for All-in-One Image Restoration](https://mlsanity.com/paper/2505.12630/) (2025)
- [Towards Unified Deep Image Deraining: A Survey and A New Benchmark](https://mlsanity.com/paper/2310.03535/) (2023)
- [Unsupervised Deraining: Where Contrastive Learning Meets Self-similarity](https://mlsanity.com/paper/2203.11509/) (2022)
- [A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applications](https://mlsanity.com/paper/2111.01968/) (2021)
- [FBNet: Feedback Network for Point Cloud Completion](https://mlsanity.com/paper/2210.03974/) (2022)
- [Networks are Slacking Off: Understanding Generalization Problem in Image Deraining](https://mlsanity.com/paper/2305.15134/) (2023)
- [Unsupervised Deraining: Where Asymmetric Contrastive Learning Meets Self-similarity](https://mlsanity.com/paper/2211.00837/) (2022)
- [Video Waterdrop Removal via Spatio-Temporal Fusion in Driving Scenes](https://mlsanity.com/paper/2302.05916/) (2023)
- [LMQFormer: A Laplace-Prior-Guided Mask Query Transformer for Lightweight Snow Removal](https://mlsanity.com/paper/2210.04787/) (2022)
- [TANet: Triplet Attention Network for All-In-One Adverse Weather Image Restoration](https://mlsanity.com/paper/2410.08177/) (2024)
- [Single Image Deraining Network with Rain Embedding Consistency and Layered LSTM](https://mlsanity.com/paper/2111.03615/) (2021)
- [Adverse Weather Optical Flow: Cumulative Homogeneous-Heterogeneous Adaptation](https://mlsanity.com/paper/2409.17001/) (2024)
- [Revisiting the Generalization Problem of Low-level Vision Models Through the Lens of Image Deraining](https://mlsanity.com/paper/2502.12600/) (2025)
- [A comprehensive benchmark analysis for sand dust image reconstruction](https://mlsanity.com/paper/2202.03031/) (2022)
- [Unsupervised Hierarchical Domain Adaptation for Adverse Weather Optical Flow](https://mlsanity.com/paper/2303.13761/) (2023)
- [Collaborative Feedback Discriminative Propagation for Video Super-Resolution](https://mlsanity.com/paper/2404.04745/) (2024)
- [TRNR: Task-Driven Image Rain and Noise Removal with a Few Images Based on Patch Analysis](https://mlsanity.com/paper/2112.01924/) (2021)
- [Global-Local Stepwise Generative Network for Ultra High-Resolution Image Restoration](https://mlsanity.com/paper/2207.08808/) (2022)
- [GAURA: Generalizable Approach for Unified Restoration and Rendering of Arbitrary Views](https://mlsanity.com/paper/2407.08221/) (2024)
- [Uncertainty-Aware Cascaded Dilation Filtering for High-Efficiency Deraining](https://mlsanity.com/paper/2201.02366/) (2022)
- [On Representation Learning with Feedback](https://mlsanity.com/paper/2202.07572/) (2022)
- [Semi-MoreGAN: A New Semi-supervised Generative Adversarial Network for Mixture of Rain Removal](https://mlsanity.com/paper/2204.13420/) (2022)
- [Asymmetric Dual-Decoder U-Net for Joint Rain and Haze Removal](https://mlsanity.com/paper/2206.06803/) (2022)
- [Potential Auto-driving Threat: Universal Rain-removal Attack](https://mlsanity.com/paper/2211.09959/) (2022)
- [Decoupling Degradation and Content Processing for Adverse Weather Image Restoration](https://mlsanity.com/paper/2312.05006/) (2023)
- [Generalizing to Out-of-Sample Degradations via Model Reprogramming](https://mlsanity.com/paper/2403.05886/) (2024)
- [Learning Dual Transformers for All-In-One Image Restoration from a Frequency Perspective](https://mlsanity.com/paper/2407.01636/) (2024)
- [SemOD: Semantic Enabled Object Detection Network under Various Weather Conditions](https://mlsanity.com/paper/2511.22142/) (2025)
- [QuReC: All-in-One Image Restoration with Query-Specific Guidance and Local-Global Response Calibration](https://mlsanity.com/paper/2607.15097/) (2026)

## Abstract (arXiv)

A deraining network can be interpreted as a conditional generator that aims at removing rain streaks from image. Most existing image deraining methods ignore model errors caused by uncertainty that reduces embedding quality. Unlike existing image deraining methods that embed low-quality features into the model directly, we replace low-quality features by latent high-quality features. The spirit of closed-loop feedback in the automatic control field is borrowed to obtain latent high-quality features. A new method for error detection and feature compensation is proposed to address model errors. Extensive experiments on benchmark datasets as well as specific real datasets demonstrate that the proposed method outperforms recent state-of-the-art methods. Code is available at:  https://github.com/LI-Hao-SJTU/DerainRLNet