35 citations · 126 across the 19 of their papers we have counts for
21 papers
HumanPhys: A Human-Centric Physical-World Perception Benchmark for Real-World Visual Reasoning
Yiming Zhang, Enzhi Zhou, Junan Lin +4
We introduce HumanPhys, a human-centric benchmark for real-world physical perception, and a training corpus emitted by the same pipeline. Each question targets a physically grounde…
Realtime-Venus: A full-duplex interaction system with asynchronous delegation
Ant Group, Ruixiang Zhao, Hualei Wang +25
Natural interaction in digital and physical environments requires continuous perception and timely responses. Spoken dialogue relies on acoustic and linguistic cues, while video in…
Leading-Silence Augmentation and Multi-Stage Synthetic Supervision for the Second MLC-SLM Challenge
Kexin Shi, Renhe Sun, Yuge Huang +4
The second Multilingual Conversational Speech Language Model (MLC-SLM) Challenge evaluates two tasks over complete, unsegmented multilingual conversations: speaker diarization and…
TranX-Adapter: Bridging Artifacts and Semantics within MLLMs for Robust AI-generated Image Detection
Wenbin Wang, Yuge Huang, Jianqing Xu +5
Rapid advances in AI-generated image (AIGI) technology enable highly realistic synthesis, threatening public information integrity and security. Recent studies have demonstrated th…
GloTok: Global Perspective Tokenizer for Image Reconstruction and Generation
Xuan Zhao, Zhongyu Zhang, Yuge Huang +6
Existing state-of-the-art image tokenization methods leverage diverse semantic features from pre-trained vision models for additional supervision, to expand the distribution of lat…
EyeSeg: An Uncertainty-Aware Eye Segmentation Framework for AR/VR
Zhengyuan Peng, Jianqing Xu, Shen Li +8
Human-machine interaction through augmented reality (AR) and virtual reality (VR) is increasingly prevalent, requiring accurate and efficient gaze estimation which hinges on the ac…
Data Synthesis with Diverse Styles for Face Recognition via 3DMM-Guided Diffusion
Yuxi Mi, Zhizhou Zhong, Yuge Huang +7
Identity-preserving face synthesis aims to generate synthetic face images of virtual subjects that can substitute real-world data for training face recognition models. While prior…
UIFace: Unleashing Inherent Model Capabilities to Enhance Intra-Class Diversity in Synthetic Face Recognition
Xiao Lin, Yuge Huang, Jianqing Xu +3
Face recognition (FR) stands as one of the most crucial applications in computer vision. The accuracy of FR models has significantly improved in recent years due to the availabilit…
Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data
Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +56
Synthetic data is gaining increasing popularity for face recognition technologies, mainly due to the privacy concerns and challenges associated with obtaining real data, including…
ID: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition
Shen Li, Jianqing Xu, Jiaying Wu +7
Synthetic face recognition (SFR) aims to generate synthetic face datasets that mimic the distribution of real face data, which allows for training face recognition models in a priv…
SlerpFace: Face Template Protection via Spherical Linear Interpolation
Zhizhou Zhong, Yuxi Mi, Yuge Huang +7
Contemporary face recognition systems use feature templates extracted from face images to identify persons. To enhance privacy, face template protection techniques are widely emplo…
Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data
Ivan DeAndres-Tame, Ruben Tolosana, Pietro Melzi +55
Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class v…
Privacy-Preserving Face Recognition Using Trainable Feature Subtraction
Yuxi Mi, Zhizhou Zhong, Yuge Huang +6
The widespread adoption of face recognition has led to increasing privacy concerns, as unauthorized access to face images can expose sensitive personal information. This paper expl…
Privacy-Preserving Face Recognition Using Random Frequency Components
Yuxi Mi, Yuge Huang, Jiazhen Ji +5
The ubiquitous use of face recognition has sparked increasing privacy concerns, as unauthorized access to sensitive face images could compromise the information of individuals. Thi…
Privacy-Preserving Face Recognition with Learnable Privacy Budgets in Frequency Domain
Jiazhen Ji, Huan Wang, Yuge Huang +6
Face recognition technology has been used in many fields due to its high recognition accuracy, including the face unlocking of mobile devices, community access control systems, and…
DuetFace: Collaborative Privacy-Preserving Face Recognition via Channel Splitting in the Frequency Domain
Yuxi Mi, Yuge Huang, Jiazhen Ji +4
With the wide application of face recognition systems, there is rising concern that original face images could be exposed to malicious intents and consequently cause personal priva…
Evaluation-oriented Knowledge Distillation for Deep Face Recognition
Yuge Huang, Jiaxiang Wu, Xingkun Xu +1
Knowledge distillation (KD) is a widely-used technique that utilizes large networks to improve the performance of compact models. Previous KD approaches usually aim to guide the st…
SDD-FIQA: Unsupervised Face Image Quality Assessment with Similarity Distribution Distance
Fu-Zhao Ou, Xingyu Chen, Ruixin Zhang +6
In recent years, Face Image Quality Assessment (FIQA) has become an indispensable part of the face recognition system to guarantee the stability and reliability of recognition perf…
CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition
Yuge Huang, Yuhan Wang, Ying Tai +5
As an emerging topic in face recognition, designing margin-based loss functions can increase the feature margin between different classes for enhanced discriminability. More recent…
Improving Face Recognition from Hard Samples via Distribution Distillation Loss
Yuge Huang, Pengcheng Shen, Ying Tai +5
Large facial variations are the main challenge in face recognition. To this end, previous variation-specific methods make full use of task-related prior to design special network l…
FAN: Feature Adaptation Network for Surveillance Face Recognition and Normalization
Xi Yin, Ying Tai, Yuge Huang +1
This paper studies face recognition (FR) and normalization in surveillance imagery. Surveillance FR is a challenging problem that has great values in law enforcement. Despite recen…