Unsupervised Learning of Spatiotemporal Features by Video Completion
In this work, we present an unsupervised representation learning approach for learning rich spatiotemporal features from videos without the supervision from semantic labels. We propose to learn the spatiotemporal features by training a 3D convolutional neural network (CNN) using video completion as...
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| Format: | Others |
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Virginia Tech
2017
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| Online Access: | http://hdl.handle.net/10919/79702 |