most citedBoosting Image Restoration via Priors from Pre-trained Models

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Dotting the Eye: An Intent-Driven Image Retouching Agent for Visual Focus Enhancement

Chujie Qin, Zilong Zhang, Zewei Chang +5

Image retouching is commonly formulated as enhancing overall visual quality through color adjustment, but in practice, it also serves to emphasize visual focus by guiding viewers'…

cs.CV2026

HDRAgent: An Agentic Framework for Multi-Exposure HDR Imaging

Weiyu Zhou, Tao Hu, Yijian Wang +3

Most existing multi-exposure HDR methods follow a fixed feed-forward reconstruction paradigm, making them prone to ghosting artifacts in complex dynamic scenes. To address this iss…

cs.CV2026

Low-Light Video Enhancement with An Effective Spatial-Temporal Decomposition Paradigm

Xiaogang Xu, Kun Zhou, Tao Hu +4

Low-Light Video Enhancement (LLVE) seeks to restore dynamic or static scenes plagued by severe invisibility and noise. In this paper, we present an innovative video decomposition s…

cs.CV2024

Low-Light Video Enhancement via Spatial-Temporal Consistent Decomposition

Xiaogang Xu, Kun Zhou, Tao Hu +4

Low-Light Video Enhancement (LLVE) seeks to restore dynamic or static scenes plagued by severe invisibility and noise. In this paper, we present an innovative video decomposition s…

cs.CV20242 cited

Boosting Image Restoration via Priors from Pre-trained Models

Xiaogang Xu, Shu Kong, Tao Hu +2

Pre-trained models with large-scale training data, such as CLIP and Stable Diffusion, have demonstrated remarkable performance in various high-level computer vision tasks such as i…