5 papers
AttriBE: Quantifying Attribute Expressivity in Body Embeddings for Recognition and Identification
Basudha Pal, Siyuan Huang, Anirudh Nanduri +2
Person re-identification (ReID) systems that match individuals across images or video frames are essential in many real-world applications. However, existing methods are often infl…
Cross-Spectral Body Recognition with Side Information Embedding: Benchmarks on LLCM and Analyzing Range-Induced Occlusions on IJB-MDF
Anirudh Nanduri, Siyuan Huang, Rama Chellappa
Vision Transformers (ViTs) have demonstrated impressive performance across a wide range of biometric tasks, including face and body recognition. In this work, we adapt a ViT model…
Multi-Domain Biometric Recognition using Body Embeddings
Anirudh Nanduri, Siyuan Huang, Rama Chellappa
Biometric recognition becomes increasingly challenging as we move away from the visible spectrum to infrared imagery, where domain discrepancies significantly impact identification…
A Quantitative Evaluation of the Expressivity of BMI, Pose and Gender in Body Embeddings for Recognition and Identification
Basudha Pal, Siyuan Huang, Rama Chellappa
Person Re-identification (ReID) systems that match individuals across images or video frames are essential in many real-world applications. However, existing methods are often infl…
MMAD-Purify: A Precision-Optimized Framework for Efficient and Scalable Multi-Modal Attacks
Xinxin Liu, Zhongliang Guo, Siyuan Huang +1
Neural networks have achieved remarkable performance across a wide range of tasks, yet they remain susceptible to adversarial perturbations, which pose significant risks in safety-…