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

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…

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 +28

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…