9 papers
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…
Subtoken Vision Transformer for Fine-grained Recognition
Jie Zhu, Ivy Zhang, Minchul Kim +1
We present Subtoken Vision Transformer (SubViT), a selective image tokenization method for fine-grained visual recognition. Standard Vision Transformers compress each fixed-size pa…
DepthAgent: Towards Better Universal Depth Estimation via Sample-wise Expert Selection
Jie Zhu, Girish Chandar Ganesan, Xiaoming Liu
Monocular metric depth estimation has achieved strong progress with large-scale training and universal-camera modeling, yet robust deployment across diverse camera settings, such a…
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…
Can Textual Reasoning Improve the Performance of MLLMs on Fine-grained Visual Classification?
Jie Zhu, Yiyang Su, Xiaoming Liu
Multi-modal large language models (MLLMs) exhibit strong general-purpose capabilities, yet still struggle on Fine-Grained Visual Classification (FGVC), a core perception task that…
GEP: A GCG-Based method for extracting personally identifiable information from chatbots built on small language models
Jieli Zhu, Vi Ngoc-Nha Tran
Small language models (SLMs) become unprecedentedly appealing due to their approximately equivalent performance compared to large language models (LLMs) in certain fields with less…
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…