Introduction
TFace: A trusty face analysis research platform developed by Tencent Youtu Lab. It provides a high-performance distributed training framework and releases our efficient methods implementations. Some of the algorithms are self-developed, and we believe the released codes benefits researchers to follow.
This project consists of several modules: Face Recognition, Face Security and Face Quality.
Face Recognition
This module implements various state-of-art algorithms for face recognition.
Paper List:
2022.9: Privacy-Preserving Face Recognition with Learnable Privacy Budgets in Frequency Domain accpted by ECCV2022.
[paper]
2022.9: DuetFace: Collaborative Privacy-Preserving Face Recognition via Channel Splitting in the Frequency Domain accepted by ACMMM2022. [paper]
2022.6: Evaluation-oriented knowledge distillation for deep face recognition accepted by CVPR2022. [paper]
2021.3: Consistent Instance False Positive Improves Fairness in Face Recognition accepted by CVPR2021. [paper]
2021.3: Spherical Confidence Learning for Face Recognition accepted by CVPR2021. [paper]
2020.8: Improving Face Recognition from Hard Samples via Distribution Distillation Loss accepted by ECCV2020. [paper]
2020.3: Curricularface: adaptive curriculum learning loss for deep face recognition has been accepted by CVPR2020. [paper]
Face Security
This module implements various state-of-art algorithms for face security.
Paper List:
2021.12: Dual Contrastive Learning for General Face Forgery Detection accepted by AAAI2022
2021.12: Exploiting Fine-grained Face Forgery Clues via Progressive Enhancement Learning accepted by AAAI2022
2021.12: Delving into the Local: Dynamic Inconsistency Learning for DeepFake Video Detection accepted by AAAI2022
2021.12: Feature Generation and Hypothesis Verification for Reliable Face Anti-Spoofing accepted by AAAI2022
2021.07: Spatiotemporal Inconsistency Learning for DeepFake Video Detection accepted by ACM MM2021[paper] [Analysis]
2021.07: Adaptive Normalized Representation Learning for Generalizable Face Anti-Spoofing accepted by ACM MM2021[paper]
2021.07: Structure Destruction and Content Combination for Face Anti-Spoofing accepted by IJCB2021[paper]
2021.04: Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition accepted by IJCAI2021[paper]
2021.04: Dual Reweighting Domain Generalization for Face Presentation Attack Detection accepted by IJCAI2021[paper]
2021.03: Delving into Data: Effectively Substitute Training for Black-box Attack accepted by CVPR2021. [paper]
2020.12: Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing accepted by AAAI2021. [paper]
2020.12: Local Relation Learning for Face Forgery Detection accepted by AAAI2021. [paper]
2020.06: Face Anti-Spoofing via Disentangled Representation Learning accepted by ECCV2020. [paper]
Face Quality
This module implements the SDD-FIQA algorithm for face quality.
Paper List:
2021.3: SDD-FIQA: Unsupervised Face Image Quality Assessment with Similarity Distribution Distance accepted by CVPR2021. [paper]