# FastDeRain: A Novel Video Rain Streak Removal Method Using Directional Gradient Priors

arXiv: https://arxiv.org/abs/1803.07487 · HTML: https://mlsanity.com/paper/1803.07487/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Mar 2018.

## Built on by (most cited first, 25 of 25)

- [RainMamba: Enhanced Locality Learning with State Space Models for Video Deraining](https://mlsanity.com/paper/2407.21773/) (2024)
- [From Sky to the Ground: A Large-scale Benchmark and Simple Baseline Towards Real Rain Removal](https://mlsanity.com/paper/2308.03867/) (2023)
- [Semi-Supervised Video Deraining with Dynamical Rain Generator](https://mlsanity.com/paper/2103.07939/) (2021)
- [Not Just Streaks: Towards Ground Truth for Single Image Deraining](https://mlsanity.com/paper/2206.10779/) (2022)
- [Enhanced Spatio-Temporal Interaction Learning for Video Deraining: A Faster and Better Framework](https://mlsanity.com/paper/2103.12318/) (2021)
- [Neural Compression-Based Feature Learning for Video Restoration](https://mlsanity.com/paper/2203.09208/) (2022)
- [DeRainGS: Gaussian Splatting for Enhanced Scene Reconstruction in Rainy Environments](https://mlsanity.com/paper/2408.11540/) (2024)
- [Neural Image Representations for Multi-Image Fusion and Layer Separation](https://mlsanity.com/paper/2108.01199/) (2021)
- [RCDNet: An Interpretable Rain Convolutional Dictionary Network for Single Image Deraining](https://mlsanity.com/paper/2107.06808/) (2021)
- [Let's See Clearly: Contaminant Artifact Removal for Moving Cameras](https://mlsanity.com/paper/2104.08852/) (2021)
- [Triple-level Model Inferred Collaborative Network Architecture for Video Deraining](https://mlsanity.com/paper/2111.04459/) (2021)
- [RainyScape: Unsupervised Rainy Scene Reconstruction using Decoupled Neural Rendering](https://mlsanity.com/paper/2404.11401/) (2024)
- [Semi-Supervised State-Space Model with Dynamic Stacking Filter for Real-World Video Deraining](https://mlsanity.com/paper/2505.16811/) (2025)
- [SiamTrans: Zero-Shot Multi-Frame Image Restoration with Pre-Trained Siamese Transformers](https://mlsanity.com/paper/2112.09426/) (2021)
- [Feature-Aligned Video Raindrop Removal with Temporal Constraints](https://mlsanity.com/paper/2205.14574/) (2022)
- [NeurTV: Total Variation on the Neural Domain](https://mlsanity.com/paper/2405.17241/) (2024)
- [Cross-Consistent Deep Unfolding Network for Adaptive All-In-One Video Restoration](https://mlsanity.com/paper/2309.01627/) (2023)
- [ASF-Net: Robust Video Deraining via Temporal Alignment and Online Adaptive Learning](https://mlsanity.com/paper/2309.00956/) (2023)
- [Fast Image-Anomaly Mitigation for Autonomous Mobile Robots](https://mlsanity.com/paper/2109.01889/) (2021)
- [EBSnoR: Event-Based Snow Removal by Optimal Dwell Time Thresholding](https://mlsanity.com/paper/2208.10581/) (2022)
- [Image Deraining via Self-supervised Reinforcement Learning](https://mlsanity.com/paper/2403.18270/) (2024)
- [Towards General and Fast Video Derain via Knowledge Distillation](https://mlsanity.com/paper/2308.05346/) (2023)
- [ViStripformer: A Token-Efficient Transformer for Versatile Video Restoration](https://mlsanity.com/paper/2312.14502/) (2023)
- [RainDancer: RGB-Event Video Deraining with Rain-Oriented Spiking Dynamics](https://mlsanity.com/paper/2607.13802/) (2026)
- [S3VD: Semantic-Guidance Spatio-Temporal Scanning for Video Deraining](https://mlsanity.com/paper/2609.21322/) (2026)

## Abstract (arXiv)

Rain streak removal is an important issue in outdoor vision systems and has recently been investigated extensively. In this paper, we propose a novel video rain streak removal approach FastDeRain, which fully considers the discriminative characteristics of rain streaks and the clean video in the gradient domain. Specifically, on the one hand, rain streaks are sparse and smooth along the direction of the raindrops, whereas on the other hand, clean videos exhibit piecewise smoothness along the rain-perpendicular direction and continuity along the temporal direction. Theses smoothness and continuity results in the sparse distribution in the different directional gradient domain, respectively. Thus, we minimize 1) the ℓ1 norm to enhance the sparsity of the underlying rain streaks, 2) two ℓ1 norm of unidirectional Total Variation (TV) regularizers to guarantee the anisotropic spatial smoothness, and 3) an ℓ1 norm of the time-directional difference operator to characterize the temporal continuity. A split augmented Lagrangian shrinkage algorithm (SALSA) based algorithm is designed to solve the proposed minimization model. Experiments conducted on synthetic and real data demonstrate the effectiveness and efficiency of the proposed method. According to comprehensive quantitative performance measures, our approach outperforms other state-of-the-art methods especially on account of the running time. The code of FastDeRain can be downloaded at https://github.com/TaiXiangJiang/FastDeRain.