4 papers
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: Benchmarking and Unifying Gait Recognition across Heterogeneous Modalities
Saihui Hou, Chenye Wang, Qingyuan Cai +2
Gait recognition is commonly studied using RGB videos or their derived silhouettes and poses. Yet human walking produces heterogeneous photometric, geometric, and motion cues that…
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…
GaitSnippet: Gait Recognition Beyond Unordered Sets and Ordered Sequences
Saihui Hou, Chenye Wang, Wenpeng Lang +2
Recent advancements in gait recognition have significantly enhanced performance by treating silhouettes as either an unordered set or an ordered sequence. However, both set-based a…