11 citations · 31 across the 15 of their papers we have counts for
16 papers · 1 filter
SapiensID 2.0: Aligning Human Recognition Foundation Models with Human Perception
Yiyang Su, Jie Zhu, Feng Liu +2
While foundation models have significantly advanced human recognition across diverse modalities, they predominantly rely on static, geometric feature extraction. This approach fund…
Non-Colliding Biometric Identities for Digital Entities: Geometry, Capacity, and Million-Scale Virtual Identity Provisioning
Yuyang Ji, Yixuan Shen, Anil Jain +2
Digital entities such as AI agents and humanoid robots increasingly operate alongside real humans, yet their identity infrastructure is based on credentials rather than embodied bi…
FusionAgent: A Multimodal Agent with Dynamic Model Selection for Human Recognition
Jie Zhu, Xiao Guo, Yiyang Su +2
Model fusion is a key strategy for robust recognition in unconstrained scenarios, as different models provide complementary strengths. This is especially important for whole-body h…
LocalScore: Local Density-Aware Similarity Scoring for Biometrics
Yiyang Su, Minchul Kim, Jie Zhu +4
Open-set biometrics faces challenges with probe subjects who may not be enrolled in the gallery, as traditional biometric systems struggle to detect these non-mated probes. Despite…
On the Holistic Approach for Detecting Human Image Forgery
Xiao Guo, Jie Zhu, Anil Jain +1
The rapid advancement of AI-generated content (AIGC) has escalated the threat of deepfakes, from facial manipulations to the synthesis of entire photorealistic human bodies. Howeve…
A Quality-Guided Mixture of Score-Fusion Experts Framework for Human Recognition
Jie Zhu, Yiyang Su, Minchul Kim +2
Whole-body biometric recognition is a challenging multimodal task that integrates various biometric modalities, including face, gait, and body. This integration is essential for ov…
Person Recognition at Altitude and Range: Fusion of Face, Body Shape and Gait
Feng Liu, Nicholas Chimitt, Lanqing Guo +16
We address the problem of whole-body person recognition in unconstrained environments. This problem arises in surveillance scenarios such as those in the IARPA Biometric Recognitio…
50 Years of Automated Face Recognition
Minchul Kim, Anil Jain, Xiaoming Liu
Over the past five decades, automated face recognition (FR) has progressed from handcrafted geometric and statistical approaches to advanced deep learning architectures that now ap…
Open-Set Biometrics: Beyond Good Closed-Set Models
Yiyang Su, Minchul Kim, Feng Liu +2
Biometric recognition has primarily addressed closed-set identification, assuming all probe subjects are in the gallery. However, most practical applications involve open-set biome…
KeyPoint Relative Position Encoding for Face Recognition
Minchul Kim, Yiyang Su, Feng Liu +2
In this paper, we address the challenge of making ViT models more robust to unseen affine transformations. Such robustness becomes useful in various recognition tasks such as face…
Learning Clothing and Pose Invariant 3D Shape Representation for Long-Term Person Re-Identification
Feng Liu, Minchul Kim, ZiAng Gu +2
Long-Term Person Re-Identification (LT-ReID) has become increasingly crucial in computer vision and biometrics. In this work, we aim to extend LT-ReID beyond pedestrian recognition…
FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude
Feng Liu, Ryan Ashbaugh, Nicholas Chimitt +17
Whole-body biometric recognition is an important area of research due to its vast applications in law enforcement, border security, and surveillance. This paper presents the end-to…
DCFace: Synthetic Face Generation with Dual Condition Diffusion Model
Minchul Kim, Feng Liu, Anil Jain +1
Generating synthetic datasets for training face recognition models is challenging because dataset generation entails more than creating high fidelity images. It involves generating…
Cluster and Aggregate: Face Recognition with Large Probe Set
Minchul Kim, Feng Liu, Anil Jain +1
Feature fusion plays a crucial role in unconstrained face recognition where inputs (probes) comprise of a set of low quality images whose individual qualities vary. Advances in…
Multi-domain Learning for Updating Face Anti-spoofing Models
Xiao Guo, Yaojie Liu, Anil Jain +1
In this work, we study multi-domain learning for face anti-spoofing(MD-FAS), where a pre-trained FAS model needs to be updated to perform equally well on both source and target dom…
Controllable and Guided Face Synthesis for Unconstrained Face Recognition
Feng Liu, Minchul Kim, Anil Jain +1
Although significant advances have been made in face recognition (FR), FR in unconstrained environments remains challenging due to the domain gap between the semi-constrained train…