4 citations · 7 across the 16 of their papers we have counts for
5 papers · 1 filter
Medical Manifestation-Aware De-Identification
Yuan Tian, Shuo Wang, Guangtao Zhai
Face de-identification (DeID) has been widely studied for common scenes, but remains under-researched for medical scenes, mostly due to the lack of large-scale patient face dataset…
R-Bench: Are your Large Multimodal Model Robust to Real-world Corruptions?
Chunyi Li, Jianbo Zhang, Zicheng Zhang +8
The outstanding performance of Large Multimodal Models (LMMs) has made them widely applied in vision-related tasks. However, various corruptions in the real world mean that images…
Free-VSC: Free Semantics from Visual Foundation Models for Unsupervised Video Semantic Compression
Yuan Tian, Guo Lu, Guangtao Zhai
Unsupervised video semantic compression (UVSC), i.e., compressing videos to better support various analysis tasks, has recently garnered attention. However, the semantic richness o…
GAIA: Rethinking Action Quality Assessment for AI-Generated Videos
Zijian Chen, Wei Sun, Yuan Tian +7
Assessing action quality is both imperative and challenging due to its significant impact on the quality of AI-generated videos, further complicated by the inherently ambiguous nat…
SMC++: Masked Learning of Unsupervised Video Semantic Compression
Yuan Tian, Xiaoyue Ling, Cong Geng +3
Most video compression methods focus on human visual perception, neglecting semantic preservation. This leads to severe semantic loss during the compression, hampering downstream v…