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ECO: Efficient Convolutional Network for Online Video Understanding
[article]
2018
arXiv
pre-print
The state of the art in video understanding suffers from two problems: (1) The major part of reasoning is performed locally in the video, therefore, it misses important relationships within actions that span several seconds. (2) While there are local methods with fast per-frame processing, the processing of the whole video is not efficient and hampers fast video retrieval or online classification of long-term activities. In this paper, we introduce a network architecture that takes long-term
arXiv:1804.09066v2
fatcat:phj7c67jrreybjjhqmnuno2cpy