5 papers
HAT: Hybrid Attention Transformer for Image Restoration
Xiangyu Chen, Xintao Wang, Wenlong Zhang +4
Transformer-based methods have shown impressive performance in image restoration tasks, such as image super-resolution and denoising. However, we find that these networks can only…
A Preliminary Exploration Towards General Image Restoration
Xiangtao Kong, Jinjin Gu, Yihao Liu +4
Despite the tremendous success of deep models in various individual image restoration tasks, there are at least two major technical challenges preventing these works from being app…
Towards Efficient SDRTV-to-HDRTV by Learning from Image Formation
Xiangyu Chen, Zheyuan Li, Zhengwen Zhang +6
Modern displays can render video content with high dynamic range (HDR) and wide color gamut (WCG). However, most resources are still in standard dynamic range (SDR). Therefore, tra…
Learning A Low-Level Vision Generalist via Visual Task Prompt
Xiangyu Chen, Yihao Liu, Yuandong Pu +4
Building a unified model for general low-level vision tasks holds significant research and practical value. Current methods encounter several critical issues. Multi-task restoratio…
A Comparative Study of Image Restoration Networks for General Backbone Network Design
Xiangyu Chen, Zheyuan Li, Yuandong Pu +4
Despite the significant progress made by deep models in various image restoration tasks, existing image restoration networks still face challenges in terms of task generality. An i…