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20242026
most citedPixel-level and Semantic-level Adjustable Super-resolution: A Dual-LoRA Approach

1 citations · 1 across the 11 of their papers we have counts for

collaborators

13 papers

cs.CV2026

PixRestore: Unified Image Restoration via Pixel Diffusion Transformer

Lingchen Sun, Rongyuan Wu, Xiangtao Kong +6

Unified image restoration (UIR) aims to recover high-quality (HQ) content from low-quality (LQ) images with different degradations using a single model. Most recent methods adapt l…

cs.CV2026

Text-Vision Co-Instructed Image Editing

Chenxi Xie, Yuhui Wu, Qiaosi Yi +1

Existing image editing methods can be generally categorized into textual instruction-based and visual prompt-based ones. Textual instructions are semantically expressive, but are l…

cs.CV2026

NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results

Xin Li, Yeying Jin, Suhang Yao +95

This paper presents an overview of the NTIRE 2026 Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images. Building upon the success of the first edition, this c…

cs.CV2026

LoViF 2026 Challenge on Real-World All-in-One Image Restoration: Methods and Results

Xiang Chen, Hao Li, Jiangxin Dong +54

This paper presents a review for the LoViF Challenge on Real-World All-in-One Image Restoration. The challenge aimed to advance research on real-world all-in-one image restoration…

cs.CV2026

GDPO-SR: Group Direct Preference Optimization for One-Step Generative Image Super-Resolution

Qiaosi Yi, Shuai Li, Rongyuan Wu +3

Recently, reinforcement learning (RL) has been employed for improving generative image super-resolution (ISR) performance. However, the current efforts are focused on multi-step ge…

cs.CV2026

CoCoEdit: Content-Consistent Image Editing via Region Regularized Reinforcement Learning

Yuhui Wu, Chenxi Xie, Ruibin Li +3

Image editing has achieved impressive results with the development of large-scale generative models. However, existing models mainly focus on the editing effects of intended object…