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most citedUCIP: A Universal Framework for Compressed Image Super-Resolution using Dynamic Prompt

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cs.CV2025

Test-Time Preference Optimization for Image Restoration

Bingchen Li, Xin Li, Jiaqi Xu +4

Image restoration (IR) models are typically trained to recover high-quality images using L1 or LPIPS loss. To handle diverse unknown degradations, zero-shot IR methods have also be…

cs.CV2025

Comp-X: On Defining an Interactive Learned Image Compression Paradigm With Expert-driven LLM Agent

Yixin Gao, Xin Li, Xiaohan Pan +7

We present Comp-X, the first intelligently interactive image compression paradigm empowered by the impressive reasoning capability of large language model (LLM) agent. Notably, com…

cs.CV2025

LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4RTX 4090s

Xijun Wang, Xin Li, Bingchen Li +1

Diffusion models have significantly advanced video super-resolution (VSR) by enhancing perceptual quality, largely through elaborately designed temporal modeling to ensure inter-fr…

cs.CV2025

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Study

Xin Li, Xijun Wang, Bingchen Li +7

In this work, we build the first benchmark dataset for short-form UGC Image Super-resolution in the wild, termed KwaiSR, intending to advance the research on developing image super…

cs.CV2025

NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results

Xin Li, Yeying Jin, Xin Jin +134

This paper reviews the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images. This challenge received a wide range of impressive solutions, which are devel…

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

Q-Adapt: Adapting LMM for Visual Quality Assessment with Progressive Instruction Tuning

Yiting Lu, Xin Li, Haoning Wu +3

The rapid advancement of Large Multi-modal Foundation Models (LMM) has paved the way for the possible Explainable Image Quality Assessment (EIQA) with instruction tuning from two p…

cs.CV2025

Hybrid Agents for Image Restoration

Bingchen Li, Xin Li, Yiting Lu +1

Existing Image Restoration (IR) studies typically focus on task-specific or universal modes individually, relying on the mode selection of users and lacking the cooperation between…