Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at https://www.ucl.ac.uk/finance/research/rs-contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
A Novel Apex-Time Network for Cross-Dataset Micro-Expression Recognition
  • Publication Type:
  • Authors:
    Peng M, Wang C, Bi T, Chen T, Zhou X, shi Y
  • Publisher:
  • Publication date:
  • Published proceedings:
    Proceedings of 8th International Conference on Affective Computing and Intelligent Interaction
  • Name of conference:
    8th International Conference on Affective Computing and Intelligent Interaction (ACII)
  • Conference place:
    Cambridge, UK
  • Conference start date:
  • Conference finish date:
  • Keywords:
  • Notes:
    6 pages, 3 figures, 3 tables, codes available
The automatic recognition of micro-expression has been boosted ever since the successful introduction of deep learning approaches. As researchers working on such topics are moving to learn from the nature of micro-expression, the practice of using deep learning techniques has evolved from processing the entire video clip of micro-expression to the recognition on apex frame. Using the apex frame is able to get rid of redundant video frames, but the relevant temporal evidence of micro-expression would be thereby left out. This paper proposes a novel Apex-Time Network (ATNet) to recognize micro-expression based on spatial information from the apex frame as well as on temporal information from the respective-adjacent frames. Through extensive experiments on three benchmarks, we demonstrate the improvement achieved by learning such temporal information. Specially, the model with such temporal information is more robust in cross-dataset validations.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Div of Psychology & Lang Sciences
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by