ActionVLAD: Learning Spatio-Temporal Aggregation for Action Classification

@article{Girdhar2017ActionVLADLS,
  title={ActionVLAD: Learning Spatio-Temporal Aggregation for Action Classification},
  author={Rohit Girdhar and Deva Ramanan and Abhinav Gupta and Josef Sivic and Bryan C. Russell},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  pages={3165-3174}
}
In this work, we introduce a new video representation for action classification that aggregates local convolutional features across the entire spatio-temporal extent of the video. We do so by integrating state-of-the-art two-stream networks [42] with learnable spatio-temporal feature aggregation [6]. The resulting architecture is end-to-end trainable for whole-video classification. We investigate different strategies for pooling across space and time and combining signals from the different… CONTINUE READING
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