17 citations · 46 across the 20 of their papers we have counts for
4 papers · 1 filter
Are Multimodal Benchmarks Really Useful? Item-Level Multimodal Benchmark Diagnosis via Structure-Response Co-Calibration
Shiqi Zhang, Weixin Zeng, Ziheng Zhang +2
Multimodal benchmarks are central to evaluating whether models can reason over information from multiple modalities. However, existing literature has revealed that some benchmarks…
MMGait: Towards Multi-Modal Gait Recognition
Chenye Wang, Qingyuan Cai, Saihui Hou +2
Gait recognition has emerged as a powerful biometric technique for identifying individuals at a distance without requiring user cooperation. Most existing methods focus primarily o…
BarbieGait: An Identity-Consistent Synthetic Human Dataset with Versatile Cloth-Changing for Gait Recognition
Qingyuan Cai, Saihui Hou, Xuecai Hu +1
Gait recognition, as a reliable biometric technology, has seen rapid development in recent years while it faces significant challenges caused by diverse clothing styles in the real…
Learning Geometric Invariance for Gait Recognition
Zengbin Wang, Junjie Li, Saihui Hou +6
The goal of gait recognition is to extract identity-invariant features of an individual under various gait conditions, e.g., cross-view and cross-clothing. Most gait models strive…