Masked Face Recognition Challenge & Workshop ICCV 2021

Abstract

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.

Links

Github Homepage including submission rules: iccv21-mfr
There're InsightFace track here and WebFace track in this workshop.

Workshop Agenda

Monday, October 11, 2021, 7:00 AM - 6:00 PM (eastern time zone)

Invited Talks

Patrick Grother: Deep Insight on Face Recognition Vendor Test
Xiaoming Liu: Trustworthy Face Recognition
Rama Chellappa: Fair Face Recognition
Jianshu Li: Face Recognition Under Financial Scenarios

Leaderboards

MS1M Track

SenseTime Research - General Model & SenseTime - SCG-STC

  • Haoyu Qin
  • Kun Hu
  • Haibo Wang
  • Yichao Wu
  • Feng Zhu
  • Zhipeng Yu
  • Ding Liang
  • Rui Zhao
  • Ao Sun
  • Baoyun Peng
  • Muxing Miao
  • Wanrong Zheng
1st place

BOE AIoT CTO

  • Jingtao Xu
  • Zhanfu An
2nd place

Alibaba DAMO Academy

  • Mang Wang
  • Liangpeng Xu
  • Tao Feng
  • Mingqian Tang
3rd place

Glint360K Track

SenseTime Group Limited - Base Model

  • Bingqi Ma
  • Yan Zhu
  • Manyuan Zhang
  • Yulun Wu
  • Guanglu Song
  • Yu Liu
1st place

SenseTime Research - General Model & SenseTime - SCG-STC

  • Haoyu Qin
  • Kun Hu
  • Haibo Wang
  • Yichao Wu
  • Feng Zhu
  • Zhipeng Yu
  • Ding Liang
  • Rui Zhao
  • Ao Sun
  • Baoyun Peng
  • Muxing Miao
  • Wanrong Zheng
2nd place

MSRA

  • Chong Li
  • Xu Yang
  • Yaoyao Chang
  • Jongyoo Kim
3rd place

Unconstrained Track

SenseTime Group Limited - Base Model

  • Manyuan Zhang
  • Bingqi Ma
  • Yunxiao Wang
  • Guanglu Song
  • Hongsheng Li
  • Yu Liu
1st place

Alibaba DAMO Academy & National University of Singapore

  • Mang Wang
  • Kai Wang
  • Liangpeng Xu
  • Tao Feng
  • Yongfei Zhao
  • Mingqian Tang
  • Yang You
2nd place

Toppan

  • Huangyi Li
3rd place

Paper

Citation:
@article{deng2021masked,
                    title={Masked Face Recognition Challenge: The InsightFace Track Report},
                    author={Deng, Jiankang and Guo, Jia and An, Xiang and Zhu, Zheng and Zafeiriou, Stefanos},
                    journal={arXiv preprint arXiv:2108.08191},
                    year={2021}
                  }