ActivityNet: A large-scale video benchmark for human activity understanding

  title={ActivityNet: A large-scale video benchmark for human activity understanding},
  author={Fabian Caba Heilbron and Victor Escorcia and Bernard Ghanem and Juan Carlos Niebles},
  journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
In spite of many dataset efforts for human action recognition, current computer vision algorithms are still severely limited in terms of the variability and complexity of the actions that they can recognize. This is in part due to the simplicity of current benchmarks, which mostly focus on simple actions and movements occurring on manually trimmed videos. In this paper we introduce ActivityNet, a new large-scale video benchmark for human activity understanding. Our benchmark aims at covering a… CONTINUE READING
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A dataset of 101 human action classes from videos in the wild

  • A.R.Z. Khurram Soomro, M. Shah
  • Technical report, University of Central Florida,
  • 2012
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