This module consists of several parts: 1. face anti-spoofing methods, 2. face forgery detection methods, 3. adversarial attack, 4. adversarial defense.
2023.09: Sibling-Attack: Rethinking Transferable Adversarial Attacks against Face Recognition accepted by CVPR2023
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] [code]
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]
- ANRL:
./tasks/Face-Anti-Spoofing/ANRL - DCN:
./tasks/Face-Anti-Spoofing/DCN
- DCL:
./tasks/Face-Forgery-Detection/DCL - STIL:
./tasks/Face-Forgery-Detection/STIL
- Adv-Makeup:
./tasks/Adv-Attack-Defense/Adv-Makeup - Sibling-Attack:
./tasks/Adv-Attack-Defense/Sibling-Attack