3 papers
cs.CV2025
Image Quality Assessment for Machines: Paradigm, Large-scale Database, and Models
Xiaoqi Wang, Yun Zhang, Weisi Lin
Machine vision systems (MVS) are intrinsically vulnerable to performance degradation under adverse visual conditions. To address this, we propose a machine-centric image quality as…
cs.CV2025
AdvDreamer Unveils: Are Vision-Language Models Truly Ready for Real-World 3D Variations?
Shouwei Ruan, Hanqing Liu, Yao Huang +5
Vision Language Models (VLMs) have exhibited remarkable generalization capabilities, yet their robustness in dynamic real-world scenarios remains largely unexplored. To systematica…
cs.CV2025
No-Reference Image Quality Assessment with Global-Local Progressive Integration and Semantic-Aligned Quality Transfer
Xiaoqi Wang, Yun Zhang
Accurate measurement of image quality without reference signals remains a fundamental challenge in low-level visual perception applications. In this paper, we propose a global-loca…