Datasets
- CVPR 2023: 5th Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW)
- ECCV 2022: 4th Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW)
- CVPR 2022: 3rd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW)
- ICCV 2021: 2nd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW)
- Synthesizing Coupled 3D Face Modalities by TBGAN
- Face Bio-metrics under COVID (Masked Face Recognition Challenge & Workshop ICCV 2021)
- First Affect-in-the-Wild Challenge
- FG-2020 Competition: Affective Behavior Analysis in-the-wild (ABAW)
- Aff-Wild2 database
- First Faces in-the-wild Workshop-Challenge
- In-The-Wild 3D Morphable Models: Code and Data
- Sound of Pixels
- Lightweight Face Recognition Challenge & Workshop (ICCV 2019)
- Audiovisual Database of Normal-Whispered-Silent Speech
- Deformable Models of Ears in-the-wild for Alignment and Recognition
- 300 Videos in the Wild (300-VW) Challenge & Workshop (ICCV 2015)
- 1st 3D Face Tracking in-the-wild Competition
- The Fabrics Dataset
- The Mobiface Dataset
- Large Scale Facial Model (LSFM)
- AgeDB
- AFEW-VA Database for Valence and Arousal Estimation In-The-Wild
- The CONFER Database
- Special Issue on Behavior Analysis "in-the-wild"
- Body Pose Annotations Correction (CVPR 2016)
- KANFace
- MeDigital
- FG-2020 Workshop "Affect Recognition in-the-wild: Uni/Multi-Modal Analysis & VA-AU-Expression Challenges"
- 4DFAB: A Large Scale 4D Face Database for Expression Analysis and Biometric Applications
- Affect "in-the-wild" Workshop
- 2nd Facial Landmark Localisation Competition - The Menpo BenchMark
- Facial Expression Recognition and Analysis Challenge 2015
- The SEWA Database
- 300 Faces In-The-Wild Challenge (300-W), IMAVIS 2014
- Mimic Me
- MAHNOB-HCI-Tagging database
- 300 Faces In-the-Wild Challenge (300-W), ICCV 2013
- MAHNOB Laughter database
- MAHNOB MHI-Mimicry database
- Facial point annotations
- MMI Facial expression database
- SEMAINE database
- iBugMask: Face Parsing in the Wild (ImaVis 2021)
- iBUG Eye Segmentation Dataset
Code
- Valence/Arousal Online Annotation Tool
- The Menpo Project
- The Dynamic Ordinal Classification (DOC) Toolbox
- Gauss-Newton Deformable Part Models for Face Alignment in-the-Wild (CVPR 2014)
- Robust and Efficient Parametric Face/Object Alignment (2011)
- Discriminative Response Map Fitting (DRMF 2013)
- End-to-End Lipreading
- DS-GPLVM (TIP 2015)
- Subspace Learning from Image Gradient Orientations (2011)
- Discriminant Incoherent Component Analysis (IEEE-TIP 2016)
- AOMs Generic Face Alignment (2012)
- Fitting AAMs in-the-Wild (ICCV 2013)
- Salient Point Detector (2006/2008)
- Facial point detector (2010/2013)
- Chehra Face Tracker (CVPR 2014)
- Empirical Analysis Of Cascade Deformable Models For Multi-View Face Detection (IMAVIS 2015)
- Continuous-time Prediction of Dimensional Behavior/Affect
- Real-time Face tracking with CUDA (MMSys 2014)
- Facial Point detector (2005/2007)
- Facial tracker (2011)
- Salient Point Detector (2010)
- AU detector (TAUD 2011)
- Action Unit Detector (2016)
- AU detector (LAUD 2010)
- Smile Detectors
- Head Nod Shake Detector (2010/2011)
- Gesture Detector (2011)
- Head Nod Shake Detector and 5 Dimensional Emotion Predictor (2010/2011)
- Gesture Detector (2010)
- HCI^2 Framework
- FROG Facial Tracking Component
- SEMAINE Visual Components (2008/2009)
- SEMAINE Visual Components (2009/2010)
Face Bio-metrics under COVID (Masked Face Recognition Challenge & Workshop ICCV 2021)
Latest News
The Masked Face Recognition Challenge & Workshop will be held in conjunction with the International Conference on Computer Vision (ICCV) 2021.
Workshop Agenda -- Monday, October 11, 2021, 7:00 AM - 6:00 PM (eastern time zone)
1. Opening Remarks (7:00AM - 7:20AM)
2. Invited Talks from Academia and Industry (~30min each + QA)
- Patrick Grother: The NIST FRVT Benchmarks: Past, Present, and Future (7:20AM - 8:00AM)
- Xiaoming Liu: Trustworthy Face Recognition (8:00AM - 8:40AM)
- Rama Chellappa
: Fair Face Recognition (9:00AM - 9:40AM) - Jianshu Li: Face Recognition Under Financial Scenarios (9:40AM - 10:20AM)
3. Top-ranked Solutions from the Challenge (SenseTime, Kakao Enterprise, Alibaba, Microsoft, DeepCam)
4. Selected Report of Workshop Papers
- Rectifying the Data Bias in Knowledge Distillation. Boxiao Liu, Shenghan Zhang, Guanglu Song, Haihang You, Yu Liu. (Best Workshop Paper)
- Boosting Fairness for Masked Face Recognition. Jun Yu, Xinlong Hao, Zeyu Cui, Peng He, Tongliang Liu. (Best Workshop Paper Runner-up)
5. Award
Workshop Video
Chairs
Jiankang Deng, Imperial College London, UK j.deng16@imperial.ac.uk
Zheng Zhu, Tsinghua University, China zhengzhu@tsinghua.edu.cn
Jia Guo, InsightFace, China guojia@gmail.com
Stefanos Zafeiriou, Imperial College London, UK s.zafeiriou@imperial.ac.uk
Scope
During the COVID-19 coronavirus epidemic, almost everyone wears a facial mask, which poses a huge challenge to face recognition. Traditional face recognition systems may not effectively recognize the masked faces, but removing the mask for authentication will increase the risk of virus infection. Inspired by the COVID-19 pandemic response, the widespread requirement that people wear protective face masks in public places has driven a need to understand how face recognition technology deals with occluded faces, often with just the periocular area and above visible.
To cope with the challenge arising from wearing masks, it is crucial to improve the existing face recognition approaches. Recently, some commercial providers have announced the availability of face recognition algorithms capable of handling face masks, and an increasing number of research publications have surfaced on the topic of face recognition on people wearing masks. However, due to the sudden outbreak of the epidemic, there is yet no publicly available masked face recognition benchmark. In this workshop, we will organise Masked Face Recognition (MFR) challenge and focus on bench-marking deep face recognition methods under the existence of facial masks.
Masked Face Recognition Challenge
InsightFace Track：Organisers
Jia Guo, InsightFace, China guojia@gmail.com
Xiang An, InsightFace, China anxiangsir@gmail.com
Zheng Zhu, Tsinghua University, China zhengzhu@tsinghua.edu.cn
Details of Insightface Track: link
WebFace Track: Organisers
Zheng Zhu, Tsinghua University, China zhengzhu@tsinghua.edu.cn
Jiagang Zhu, China jiagang.zhu@xforwardai.com
Jia Guo, InsightFace, China guojia@gmail.com
Details of WebFace Track: link
Leaderboard
Insightface and WebFace
Online Discussion for Challenge:
Check this link for the challenge tips and further discussions.
Challenge & Workshop Paper Submission:
Challenge participants can submit a paper to summarize the methodology and the achieved performance of their algorithm. We also welcome other face-related research works to submit to this workshop. Submissions should adhere to the main ICCV 2021 proceedings style. The workshop papers will be published in the ICCV 2021 proceedings. Please sign up in the submission system to submit your paper.
Important Dates:
- 1 June - Announcement of the Challenge
- 1 June - Release of the training data, baseline solutions and testing leader-board
- 3 August - Workshop paper submission deadline
- 8 August - Final decision on submitted workshop papers
- 15 August - Deadline for camera-ready of workshop papers
- 1 October - Stop leader-board submission (11:59 PM Pacific Time)
- 11 October - Workshop day 7:00 AM - 6:00 PM (eastern time zone).
Sponsors:
The Masked Face Recognition Challenge has been supported by (in alphabetical order)
Kiwi Tech （5000$）
OneFlow （5000$）
XforwardAI (7750$)
Zoloz（5000$）
Dynamic funding pool: (22,750$)
Contact:
InsightFace Track: insightface.challenge@gmail.com
WebFace Track: info@face-benchmark.org