activity
20242026
collaborators

7 papers

cs.CV2026

SteerFace: Debiasing Synthetic Face Generation via Adaptive Residue Perturbation

Yuxi Mi, Qiuyang Yuan, Jianqing Xu +5

The shortage of legally compliant data for face recognition training has sparked growing interest in using synthetic data as an alternative. While recent diffusion-based methods en…

cs.CV2026

ImmerIris: A Large-Scale Dataset and Benchmark for Off-Axis and Unconstrained Iris Recognition in Immersive Applications

Yuxi Mi, Qiuyang Yuan, Zhizhou Zhong +5

Recently, iris recognition is regaining prominence in immersive applications such as extended reality as a means of seamless user identification. This application scenario introduc…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…