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Fast Video Salient Object Detection via Spatiotemporal Knowledge Distillation
[article]
2021
arXiv
pre-print
Since the wide employment of deep learning frameworks in video salient object detection, the accuracy of the recent approaches has made stunning progress. These approaches mainly adopt the sequential modules, based on optical flow or recurrent neural network (RNN), to learn robust spatiotemporal features. These modules are effective but significantly increase the computational burden of the corresponding deep models. In this paper, to simplify the network and maintain the accuracy, we present a
arXiv:2010.10027v2
fatcat:rvdln7uz2rgb5ipvsswv7yntsi