First Faces in-the-wild Workshop-Challenge

We are running the first Faces-in-the-Wild Workshop-Challeng

Latest News

 We also welcome papers in all aspects of face analysis in-the-wild (including but not limited to face and facial expression recognition etc.)




Stefanos Zafeiriou, Imperial College London, UK                      

Mihalis Nicolaou, Goldsmiths University of London, UK                       

 Irene Kotsia, Hellenic Open University, Greeece,                         

Fabian Benitez-Quiroz,  Ohio State University, USA                   

Guoying Zhao, University of Oulu,                                               

Maja Pantic, Imperial College London,                                       

Data Chairs:

Dimitris Kollias, Athanasios Papaioannou, Grygorios Chrysos, Georgios Trigeorgis, Jiakang Deng, Jie Shen,  

Scope of the challenges

Affect in the wild Challenge:The human Face is arguably the most studied object in computer vision. Recently, tens of databases have been collected under unconstrained conditions (also referred to as “in-thewild”) for many face related task such as face detection, face verification and facial landmark localisation. However, well-established databases and benchmarks “in-the-wild” do not exist, specifically for problems such as  estimation of affect in a continuous dimensional space (e.g., valence and arousal) in videos displaying spontaneous facial behaviour. In CVPR 2017, we propose to make a significant step further and propose new comprehensive benchmarks for assessing the performance of facial affect/behaviour analysis/understanding “in-the-wild”. To the best of our knowledge, this is the first time that an attempt for benchmarking the efforts of valence and arousal "in-the-wild". 

For more information please visit the challenge webpage. 

2nd Face alignment in-the-wild:  Currently comprehensive benchmarks exist for facial landmark localization and tracking (see 300W [1] and 300VW [5] challenges). Nevertheless, these benchmarks are mainly about (near) frontal faces. In CVPR 2017, we make a significant step further and present a new comprehensive multi-pose benchmark, as well as organize a workshop-challenge for landmark detection in images displaying arbitrary poses. To this end we have annotated a large set of profile faces with 39 fiducial points. Furthermore, we have annotated many new images of (near) frontal faces using the standard 68 point markup.  The challenge will represent the very first thorough quantitative evaluation on multipose face landmark detection. Furthermore, the competition will explore how far we are from attaining satisfactory facial landmark localisation in arbitrary poses. The results of the Challenge will be presented at the  Faces " in-the-wild" (Wild-Face) Workshop to be held in conjunction with CVPR 2017.

For more information please visit the challenge webpage. 


Faces in-the-wild 2017 Workshop

Our aim is to accept up to 10 papers to be orally presented at the workshop and another 10 as posters.  


Submission Information:

Challenge participants should submit a paper to the Faces-in-the-wild Workshop, which summarises the methodology and the achieved performance of their algorithm. Submissions should adhere to the main CVPR 2017 proceedings style. The workshop papers will be published in the CVPR 2017 proceedings. Please sign up in the submissions system to submit your paper.

Important Dates:

  • 27 January: Announcement of the Challenges
  • 30 January: Release of first batch of the training videos
  • 20 March:  Release of the test data
  • 27 March: Deadline of returning results
  • 1 April: Return of the results to authors
  • 20 April: Deadline for paper submission
  • 27 April: Decisions 
  • 19 May: Camera-ready deadline
  • 26 July: Workshop date




Program Committee:

  • Jorge Batista, University of Coimbra (Portugal)
  • Richard Bowden, University of Surrey (UK)
  • Jeff Cohn, CMU/University of Pittsburgh (USA)
  • Roland Goecke, University of Canberra (AU)
  • Peter Corcoran, NUI Galway (Ireland)
  • Fred Nicolls, University of Cape Town (South Africa)
  • Mircea C. Ionita, Daon (Ireland)
  • Ioannis Kakadiaris, University of Houston (USA)
  • Stan Z. Li, Institute of Automation Chinese Academy of Sciences (China)
  • Simon Lucey, CMU (USA)
  • Iain Matthews, Disney Research (USA)
  • Aleix Martinez, University of Ohio (USA)
  • Dimitris Metaxas, Rutgers University (USA)
  • Stephen Milborrow,            
  • Louis P. Morency, University of South California (USA)      
  • Ioannis Patras, Queen Mary University (UK)      
  • Matti Pietikainen, University of Oulu (Finland)  
  • Deva Ramaman, University of Irvine (USA)
  • Jason Saragih, Commonwealth Sc. & Industrial Research Organisation (AU) 
  • Nicu Sebe, University of Trento (Italy)
  • Jian Sun, Microsoft Research Asia
  • Xiaoou Tang, Chinese University of Hong Kong (China)
  • Fernando De La Torre, Carnegie Mellon University (USA)
  • Philip A. Tresadern, University of Manchester (UK)
  • Michel Valstar, University of Nottingham (UK)
  • Xiaogang Wang, Chinese University of Hong Kong (China)
  • Fang Wen, Microsoft Research Asia
  • Lijun Yin, Binghamton University (USA)



This challenges have been supported by a distinguished fellowship to Dr. Stefanos Zafeiriou by TEKES and EPSRC Projects FACER2VM and H2020 TESLA.