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Learning Video Object Segmentation with Visual Memory
[article]
2017
arXiv
pre-print
This paper addresses the task of segmenting moving objects in unconstrained videos. We introduce a novel two-stream neural network with an explicit memory module to achieve this. The two streams of the network encode spatial and temporal features in a video sequence respectively, while the memory module captures the evolution of objects over time. The module to build a "visual memory" in video, i.e., a joint representation of all the video frames, is realized with a convolutional recurrent unit
arXiv:1704.05737v2
fatcat:aoyzqp2bdrctld6a5n6et3tzby