collaborators

8 papers

eess.IV2026

CompressedVQA-AEV: Full-Reference and No-Reference Quality Assessment Models for Asymmetric Encoded Videos

Wei Sun, Xingwei Liu, Dandan Zhu +3

This report presents our solutions to the QoMEX 2026 Grand Challenge on Video Quality Assessment for Asymmetric Encoded Videos, comprising a full-reference (FR) model, CompressedVQ…

cs.CV2026

LEIQ-Assessor: Multi-dimensional Quality Assessment of Low-light Enhanced Images via Multi-task Learning

Wei Sun, Yanwei Jiang, Dandan Zhu +4

Low-light image enhancement algorithms (LIEAs) aim to improve the visibility of images captured under poor illumination. However, the enhancement process often introduces artifacts…

cs.CV2026

Hyperbolic and Evidence-Prioritized Experts for Large Vision-Language Models

Zijie Zhou, Dandan Zhu, Hangxiangpan Wang +3

Large Vision-Language Models (LVLMs) have demonstrated impressive performance on multimodal tasks through scaled architectures and extensive training. Recent studies introduce Mixt…

cs.CV2026

NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)

Guanyi Qin, Jie Liang, Bingbing Zhang +50

In this paper, we present an overview of the NTIRE 2026 challenge on the 3rd Restore Any Image Model in the Wild, specifically focusing on Track 1: Professional Image Quality Asses…

cs.CV2026

LoViF 2026 Challenge on Human-oriented Semantic Image Quality Assessment: Methods and Results

Xin Li, Daoli Xu, Wei Luo +27

This paper reviews the LoViF 2026 Challenge on Human-oriented Semantic Image Quality Assessment. This challenge aims to raise a new direction, i.e., how to evaluate the loss of sem…

cs.CV2026

DP^2-VL: Private Photo Dataset Protection by Data Poisoning for Vision-Language Models

Hongyi Miao, Jun Jia, Xincheng Wang +7

Recent advances in visual-language alignment have endowed vision-language models (VLMs) with fine-grained image understanding capabilities. However, this progress also introduces n…

cs.AI2026

LifeEval: A Multimodal Benchmark for Assistive AI in Egocentric Daily Life Tasks

Hengjian Gao, Kaiwei Zhang, Shibo Wang +8

The rapid progress of Multimodal Large Language Models (MLLMs) marks a significant step toward artificial general intelligence, offering great potential for augmenting human capabi…

cs.CV2025

Generalizable Video Quality Assessment via Weak-to-Strong Learning

Linhan Cao, Wei Sun, Xiangyang Zhu +6

Video quality assessment (VQA) seeks to predict the perceptual quality of a video in alignment with human visual perception, serving as a fundamental tool for quantifying quality d…