no code implementations • 30 Nov 2017 • Behrooz Mahasseni, Xiaodong Yang, Pavlo Molchanov, Jan Kautz
In this paper, we address the challenging problem of efficient temporal activity detection in untrimmed long videos.
no code implementations • CVPR 2017 • Behrooz Mahasseni, Sinisa Todorovic, Alan Fern
In this work, we study a poorly understood trade-off between accuracy and runtime costs for deep semantic video segmentation.
no code implementations • CVPR 2017 • Michael Lam, Behrooz Mahasseni, Sinisa Todorovic
This motivates us to formulate our problem as a sequential search for informative parts over a deep feature map produced by a deep Convolutional Neural Network (CNN).
1 code implementation • CVPR 2017 • Behrooz Mahasseni, Michael Lam, Sinisa Todorovic
The summarizer is the autoencoder long short-term memory network (LSTM) aimed at, first, selecting video frames, and then decoding the obtained summarization for reconstructing the input video.
no code implementations • 26 Jul 2016 • Behrooz Mahasseni, Sinisa Todorovic, Alan Fern
Our second contribution is the algorithm for learning a policy for the sparse selection of supervoxels and their descriptors for budgeted CRF inference.
no code implementations • CVPR 2016 • Behrooz Mahasseni, Sinisa Todorovic
This paper argues that large-scale action recognition in video can be greatly improved by providing an additional modality in training data -- namely, 3D human-skeleton sequences -- aimed at complementing poorly represented or missing features of human actions in the training videos.