Enhancing Face Anti-Spoofing with Swin Transformer-driven Multi-stage Pipeline

Author:

Thai Son1ORCID,Bui Hop2ORCID,Vu Huy2ORCID,Nguyen Khanh3ORCID,Huynh Tin1ORCID,Hoang Kiem1ORCID

Affiliation:

1. The Saigon International University, Viet Nam

2. VNU-HCM University of Science, Viet Nam

3. VNU-HCM University of Information Technology, Viet Nam

Publisher

ACM

Reference29 articles.

1. Face anti-spoofing using patch and depth-based CNNs

2. LBP − TOP Based Countermeasure against Face Spoofing Attacks

3. Alexey Dosovitskiy , Lucas Beyer , Alexander Kolesnikov , Dirk Weissenborn , Xiaohua Zhai , Thomas Unterthiner , Mostafa Dehghani , Matthias Minderer , Georg Heigold , Sylvain Gelly , 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 ( 2020 ). Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, 2020. An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020).

4. On the Effectiveness of Vision Transformers for Zero-shot Face Anti-Spoofing

5. Face Anti-Spoofing Using CNN Classifier & Face liveness Detection

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