A survey on deep learning based approaches for action and gesture recognition in image sequences



The interest in action and gesture recognition has grown considerably in the last years. In this paper, we present a survey on current deep learning methodologies for action and gesture recognition in image sequences. We introduce a taxonomy that summarizes important aspects of deep learning for approaching both tasks. We review the details of the proposed architectures, fusion strategies, main datasets, and competitions. We summarize and discuss the main works proposed so far with particular interest on how they treat the temporal dimension of data, discussing their main features and identify opportunities and challenges for future research.


Hugo Jair Escalante
Shohreh Kasaei
Marco Bellantonio
Sergio Escalera
Víctor Ponce-López
Xavier Baró
Isabelle Guyon
Maryam Asadi-Aghbolaghi
Isabelle Guyon