A Collection of Papers and Codes for ECCV2024/ECCV2020 Low Level Vision

[ECCV 2024] SMFANet: A Lightweight Self-Modulation Feature Aggregation Network for Efficient Image Super-Resolution

[ECCV 2024] SMFANet: A Lightweight Self-Modulation Feature Aggregation Network for Efficient Image Super-Resolution

[CVPR2023] Blur Interpolation Transformer for Real-World Motion from Blur

The official implementation of the paper of CVPR2024: Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model

[ECCV2022] "Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression", https://arxiv.org/abs/2207.10564

Towards Ultra-High-Definition Image Deraining: A Benchmark and An Efficient Method

A paper list of recent mamba efforts for low-level vision.

handy tools for user study

Learning An Effective Transformer for Remote Sensing Satellite Image Dehazing

Learning A Spiking Neural Network for Efficient Image Deraining (IJCAI 2024)

This is a summary of research on All-In-One Image/Video Restoration. There may be omissions. If anything is missing please get in touch with us. Our emails: [email protected]; gouyuanbiao@gmail.…

Event camera (DVS, Spike) based Papers Published on Top International Conference

ACM MM'23 | The office repository of NightHazeFormer: Single Nighttime Haze Removal Using Prior Query Transformer

[Mamba-Survey-2024] Paper list for State-Space-Model/Mamba and it's Applications

CM-GAN for Image Inpainting

ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting (NeurIPS 2023 Spotlight)

[ECCV 2022] LEDNet: Joint Low-light Enhancement and Deblurring in the Dark

[CVPR2024] SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution

Maximize Efficiency, Elevate Accuracy: Slash GPU Hours by Half with Efficient Pre-training!

Adapt or Perish: Adaptive Sparse Transformer with Attentive Feature Refinement for Image Restoration

Rethinking Multi-Scale Representations in Deep Deraining Transformer

SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild