3 citations · 3 across the 5 of their papers we have counts for
6 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…
Template-based Multi-Domain Face Recognition
Anirudh Nanduri, Rama Chellappa
Despite the remarkable performance of deep neural networks for face detection and recognition tasks in the visible spectrum, their performance on more challenging non-visible domai…
A Fast and Accurate System for Face Detection, Identification, and Verification
Rajeev Ranjan, Ankan Bansal, Jingxiao Zheng +7
The availability of large annotated datasets and affordable computation power have led to impressive improvements in the performance of CNNs on various object detection and recogni…
UMDFaces: An Annotated Face Dataset for Training Deep Networks
Ankan Bansal, Anirudh Nanduri, Carlos Castillo +2
Recent progress in face detection (including keypoint detection), and recognition is mainly being driven by (i) deeper convolutional neural network architectures, and (ii) larger d…