Many human actions, such as "playing violin" and "taking a photo", are well described by still images. Recognizing human actions and estimating human poses in still images will potentially provide useful information in image indexing and visual search, since a large proportion of available images contain people. Progress on these tasks is also beneficial to object and scene recognition, given the frequent human-object and human-scene interactions. Furthermore, as video processing algorithms often rely on some form of initialization from individual video frames, it would be interesting to have a better understanding of how, when, and to what extent static information can help recognize human actions and estimate human pose in videos. This workshop offers a great opportunity to bring together researchers and experts working on different aspects of action recognition and pose estimation to demonstrate their recent work. It provides a common playground for inspiring discussions and stimulating debates. Specifically, the workshop will focus on the following aspects.
- Human pose estimation in still images
- Human action recognition in still images
- Modeling and recognition of human-object interactions
- Scene context for human poses and actions
- Understanding humans in videos or depth images
- Novel datasets of human poses or actions
- Actions and human pose research in cognitive psychology / human perception
Please click here to view our call for papers in PDF.
David Forsyth, University of Illinois at Urbana-Champaign, USA
Abhinav Gupta, Carnegie Mellon University, USA
Jitendra Malik, University of California, Berkeley, USA
Aude Oliva, Massachusetts Institute of Technology, USA
Deva Ramanan, University of California, Irvine, USA
Jamie Shotton, Microsoft Research Cambridge, UK