Showing cs.CVShow all
3 papers · 1 filter
cs.CV2025
Segmenting and Understanding: Region-aware Semantic Attention for Fine-grained Image Quality Assessment with Large Language Models
Chenyue Song, Chen Hui, Haiqi Zhu +4
No-reference image quality assessment (NR-IQA) aims to simulate the process of perceiving image quality aligned with subjective human perception. However, existing NR-IQA methods e…
cs.CV2025
Q-CLIP: Unleashing the Power of Vision-Language Models for Video Quality Assessment through Unified Cross-Modal Adaptation
Yachun Mi, Yu Li, Yanting Li +6
Accurate and efficient Video Quality Assessment (VQA) has long been a key research challenge. Current mainstream VQA methods typically improve performance by pretraining on large-s…
cs.CV2025
BPCLIP: A Bottom-up Image Quality Assessment from Distortion to Semantics Based on CLIP
Chenyue Song, Chen Hui, Wei Zhang +4
Image Quality Assessment (IQA) aims to evaluate the perceptual quality of images based on human subjective perception. Existing methods generally combine multiscale features to ach…