most citedDiff-Restorer: Unleashing Visual Prompts for Diffusion-based Universal Image Restoration

2 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2025

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results

Xin Li, Kun Yuan, Bingchen Li +110

This paper presents a review for the NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement. The challenge comprises two tracks: (i) Efficient Video Qualit…

cs.CV2025

Distillation-Supervised Convolutional Low-Rank Adaptation for Efficient Image Super-Resolution

Xinning Chai, Yao Zhang, Yuxuan Zhang +4

Convolutional neural networks (CNNs) have been widely used in efficient image super-resolution. However, for CNN-based methods, performance gains often require deeper networks and…

cs.CV2025

The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report

Bin Ren, Hang Guo, Lei Sun +143

This paper presents a comprehensive review of the NTIRE 2025 Challenge on Single-Image Efficient Super-Resolution (ESR). The challenge aimed to advance the development of deep mode…

cs.CV2025

Enhanced Semantic Extraction and Guidance for UGC Image Super Resolution

Yiwen Wang, Ying Liang, Yuxuan Zhang +6

Due to the disparity between real-world degradations in user-generated content(UGC) images and synthetic degradations, traditional super-resolution methods struggle to generalize e…

cs.CV20242 cited

Diff-Restorer: Unleashing Visual Prompts for Diffusion-based Universal Image Restoration

Yuhong Zhang, Hengsheng Zhang, Xinning Chai +4

Image restoration is a classic low-level problem aimed at recovering high-quality images from low-quality images with various degradations such as blur, noise, rain, haze, etc. How…

cs.CV2024

Multimodal Semantic-Aware Automatic Colorization with Diffusion Prior

Han Wang, Xinning Chai, Yiwen Wang +3

Colorizing grayscale images offers an engaging visual experience. Existing automatic colorization methods often fail to generate satisfactory results due to incorrect semantic colo…