https://github.com/syy-whu/drd-net
공식 코드Detail-recovery Image Deraining via Dual Sample-augmented Contrastive Learning
Papers with Code 아카이브
Rain Removal
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/syy-whu/semi-moregan
공식 코드Semi-MoreGAN: A New Semi-supervised Generative Adversarial Network for Mixture of Rain Removal
https://github.com/taowangzj/gridformer
공식 코드https://github.com/tombs98/mhnet
공식 코드https://github.com/tsingqguo/efficientderain
공식 코드EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining
https://github.com/txphome/dfpir
공식 코드Degradation-Aware Feature Perturbation for All-in-One Image Restoration
https://github.com/va1shn9v/promptir
공식 코드https://github.com/vcl3d/cmudrn
공식 코드Cross-Stitched Multi-task Dual Recursive Networks for Unified Single Image Deraining and Desnowing
https://github.com/wlydlut/c2f-dft
공식 코드Learning A Coarse-to-Fine Diffusion Transformer for Image Restoration
https://github.com/wlydlut/uhd-image-restoration-survey
공식 코드Deep Learning-Driven Ultra-High-Definition Image Restoration: A Survey
https://github.com/wlydlut/uhddip
공식 코드Ultra-High-Definition Image Restoration: New Benchmarks and A Dual Interaction Prior-Driven Solution
https://github.com/yc-liang/drt
공식 코드DRT: A Lightweight Single Image Deraining Recursive Transformer
https://github.com/yechanp/MCW-Net
공식 코드MCW-Net: Single Image Deraining with Multi-level Connections and Wide Regional Non-local Blocks
https://github.com/yluestc/derain
공식 코드https://github.com/yt3dvision/4d-mgp-srrnet
공식 코드Rain Removal from Light Field Images with 4D Convolution and Multi-scale Gaussian Process
https://github.com/yunguo224/NLCL
공식 코드Unsupervised Deraining: Where Contrastive Learning Meets Self-similarity
https://github.com/yunguo224/lhp-rain
공식 코드From Sky to the Ground: A Large-scale Benchmark and Simple Baseline Towards Real Rain Removal
https://github.com/yunguo224/ug2_deraining
공식 코드https://github.com/yuyi-sd/robust_rain_removal
공식 코드https://github.com/yz-wang/demore-net
공식 코드Joint Depth Estimation and Mixture of Rain Removal From a Single Image
https://github.com/yz-wang/togethernet
공식 코드https://github.com/zhangyi-3/kbnet
공식 코드https://github.com/zjlab-ammi/restormer-plus
공식 코드https://github.com/zsyOAOA/S2VD
공식 코드Semi-Supervised Video Deraining with Dynamical Rain Generator
https://github.com/ztmotalee/regformer
공식 코드Exploiting Regional Information Transformer for Single Image Deraining
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/IPT
https://github.com/2023-MindSpore-1/ms-code-216/tree/main/SDNet
https://github.com/2023-MindSpore-4/Code11/tree/main/SDNet
https://github.com/Aitical/PCL-SISR
Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration
https://github.com/GarrickZ2/Image-Denoising
Restormer: Efficient Transformer for High-Resolution Image Restoration
https://github.com/GuoQuanhao/PRNet-Paddle
Progressive Image Deraining Networks: A Better and Simpler Baseline
https://github.com/HDCVLab/MC-Blur-Dataset
https://github.com/He-jerry/De-raining-gan
Image De-raining Using a Conditional Generative Adversarial Network
https://github.com/He-jerry/Residual-SE-Network
Residual Squeeze-and-Excitation Network for Fast Image Deraining
https://github.com/Leozhibin/PReNet-master
Progressive Image Deraining Networks: A Better and Simpler Baseline
https://github.com/MKFMIKU/VIDM
Restormer: Efficient Transformer for High-Resolution Image Restoration
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.