Welcome to the 6th Face Anti-Spoofing Workshop:
Unified Physical-Digital Attacks Detection@ICCV2025
Afternoon, 19 October, 2025 ICCV
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The 6th Face Anti-Spoofing Workshop: Unified Physical-Digital Attacks Detection@ICCV2025
Introduction
In recent years, the growing sophistication of face spoofing techniques has significantly threatened the security of face recognition systems. Face Anti-Spoofing (FAS) has thus become a critical component in ensuring the reliability of biometric authentication. To stimulate research in this area, we have organized five successful editions of the Face Anti-Spoofing Workshop and Challenge at major conferences, including CVPR 2019, CVPR 2020, ICCV 2021, CVPR 2023, and CVPR 2024, attracting over 1,400 participating teams from academia and industry. However, unified detection of both physical and digital attacks remains a major challenge. While physical presentation attacks such as print, replay, and 3D mask attacks typically introduce artifacts like color distortion and moiré patterns, digital forgeries—including identity manipulations, adversarial examples, and GAN-based generation—alter facial imagery at the pixel level in often imperceptible ways. Existing solutions still treat these as separate tasks, hindering the development of generalizable models. To address this gap, the 6th Face Anti-Spoofing Workshop@ICCV 2025 introduces the task of Unified Physical-Digital Attack Detection and releases a significantly expanded dataset, UniAttackData+. We collected data from 2,875 participants representing three distinct ethnic groups (i.e., African, East Asian, and Central Asian), capturing 18,250 authentic videos under various lighting conditions, backgrounds, and acquisition devices. For each participant, we applied 54 different attack methods, including 14 physical attacks and 40 digital attacks, resulting in a total of 679,097 forged videos.
Challenge website: [Link]
Workshop Paper Submission Link: Waiting for opening......
Ref:
[1] Ajian Liu, Haocheng Yuan, Xiao Guo, Hui Ma, Wanyi Zhuang, Changtao Miao, Jun Lan, Qi Chu, Jun Wan, Xiaoming Liu, Zhen Lei Benchmarking Unified Face Attack Detection via Hierarchical Prompt Tuning. [Link]
Workshop Schedule
Date: Oct. 19th, 2025
Current Start Time: October 19, 2025 at 01:00 PM HST ——Current End Time: October 19, 2025 at 05:00 PM HST
Location:
13:00 – 13:20 Opening & Workshop Overview (hosts introduce organizing units, partners, dataset, competition, and results)
13:20 – 13:25 Introduction of 1st place team: Tencent Youtu
13:25 – 13:45 Tencent Youtu presentation (20 minutes)
13:45 – 13:50 Q&A for Tencent Youtu (5 minutes)
13:50 – 13:55 Award presentation to Tencent Youtu
13:55 – 14:00 Introduction of 2nd place team: TeleAI
14:00 – 14:20 TeleAI presentation (20 minutes)
14:20 – 14:25 Q&A for TeleAI (5 minutes)
14:25 – 14:30 Award presentation to TeleAI
14:30 – 14:35 Introduction of 3rd place team: Akuvox
14:35 – 14:55 Akuvox presentation (20 minutes)
14:55 – 15:00 Q&A for Akuvox (5 minutes)
15:00 – 15:10 Coffee break
15:10 – 15:15 Introduction of Keynote Speaker 1
15:15 – 15:50 Keynote Speaker 1 presentation (35 minutes)
15:50 – 15:55 Q&A for Keynote Speaker 1 (5 minutes)
15:55 – 16:00 Introduction of Keynote Speaker 2
16:00 – 16:35 Keynote Speaker 2 presentation (35 minutes)
16:35 – 16:40 Q&A for Keynote Speaker 2 (5 minutes)
16:40 – 16:50 Discussion of future work
16:50 – 17:00 Closing
Important Competition Dates:
20 May 2025: Quantitative competition begins; Development data released: training set with true labels; Validation data released: validation set without true labels; Encrypted test data released (no labels provided).
12 June 2025: Release of encrypted final evaluation data (test data without true labels); True labels of validation set released.
13 June 2025: Release of final evaluation data decryption key; Participants start predicting results on the final evaluation data.
28 June 2025: Quantitative competition ends; Deadline for submitting final predictions on test data; Deadline for code submission (organizers verify code on test data).
30 June 2025: Challenge results officially released.
9 July 2025: Deadline for workshop paper submissions.
11 July 2025: Deadline for authors to submit meta-data of accepted papers.
18 August 2025: Camera-ready paper submission deadline.
19 October 2025: Workshop@ICCV 2025 held; Challenge results announced; Award ceremony conducted.
Keynote Speakers:
Pong C Yuen received his Ph.D. degree in Electrical and Electronic Engineering from The University of Hong Kong. He joined the Hong Kong Baptist University in 1993, served as the Head of Department of Computer Science from 2011 – 2017 and Associate Dean (Teaching and Learning) of Faculty of Science from 2018-2024. Currently, he is a Chair Professor in Computer Science, Hong Kong Baptist University.
Over the years, Dr. Yuen has spent his sabbatical and visited a number of universities/research institutes as a visiting professor/scholar, including The University of Sydney (Australia), The University of Maryland at College Park (USA), INRIA Rhone Alpes (France), ETH Zurich (Switzerland), and The University of Bologna (Italy). Dr. Yuen was the director of Croucher Advanced Study Institute (ASI) on biometric authentication in 2004 and the director of Croucher ASI on Biometric Security and Privacy in 2007. He has been serving as the Director of IAPR/IEEE Winter School on Biometrics since 2017.
Zhen Lei, IEEE Fellow, IAPR Fellow, is a Professor at the Institute of Automation, Chinese Academy of Sciences (CASIA), and at the School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS).
His research interests include biometrics, intelligent video analysis, and fundamental theories of artificial intelligence. He has led and participated in major national projects such as the National Key R&D Program of China and the National Natural Science Foundation of China.
Dr. Lei has published over 200 papers in leading journals and conferences, including nine papers in IEEE TPAMI, and more than 60 in CCF-A venues. He has received four Best Paper/Best Student Paper Awards at flagship conferences and achieved seven first-place results in international vision competitions. He holds over 30 invention patents and has contributed to two national standards and seven industry standards.
With more than 32,000 citations and an H-index of 85, he has been recognized as an Elsevier Highly Cited Chinese Researcher (2020–2023) and listed among the World’s Top 2% Scientists. His honors include the 2019 IAPR Young Biometrics Investigator Award, the 2019 National Science and Technology Progress Award (Second Prize), the 2021 China Institute of Electronics Technical Invention Award (First Prize), and the 2022 CSIG Natural Science Award (Second Prize). He has also received the Outstanding Contribution Award of the Beijing Olympic and Paralympic Games, the Barcelona Global Smart City Project Finalist Award, and the Huawei Excellent Technical Cooperation Achievement Award (2020).
Siwei Lyu (pending) is a SUNY Distinguished Professor and Empire Innovation Professor at the University at Buffalo, where he directs the UB Media Forensic Lab and co-directs the Center for Information Integrity. His research focuses on media forensics, computer vision, and machine learning.
He has published over 240 papers and received funding from NSF, DARPA, and the U.S. Department of Homeland Security. His honors include the NSF CAREER Award, IEEE Best Paper Award, and the Google Faculty Research Award. Dr. Lyu is a Fellow of IEEE, IAPR, and AAIA, and a Distinguished Member of ACM.
Organizers:
Jun Wan (万军 Primary Contact), Institute of Automation, Chinese Academy of Sciences (CASIA), China, jun.wan@ia.ac.cn
Jiankang Deng, Insightface, jiankangdeng@gmail.com
Jun Lan, Ant Group, China, yelan.lj@antgroup.com
Weiqiang Wang, Ant Group, China, weiqiang.wwq@antgroup.com
Sergio Escalera, Computer Vision Center (UAB) and University of Barcelona, Spain, sergio@maia.ub.es
Hugo Jair Escalante, INAOE, ChaLearn, Mexico, hugojair@inaoep.mx
Xiaoming Liu, Michigan State University (MSU), USA, liuxm@msu.edu
Ajian Liu, Institute of Automation, Chinese Academy of Sciences (CASIA), China, ajian.liu@ia.ac.cn
Zhen Lei, Institute of Automation, Chinese Academy of Sciences (CASIA), China, zhen.lei@ia.ac.cn
Isabelle Guyon, Université Paris-Saclay, France and ChaLearn, Berkeley, California, USA, guyon@chalearn.org
Organizers Institutions:
Google Sites
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