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Action Localization through Continual Predictive Learning
[article]
2020
arXiv
pre-print
The problem of action recognition involves locating the action in the video, both over time and spatially in the image. The dominant current approaches use supervised learning to solve this problem, and require large amounts of annotated training data, in the form of frame-level bounding box annotations around the region of interest. In this paper, we present a new approach based on continual learning that uses feature-level predictions for self-supervision. It does not require any training
arXiv:2003.12185v1
fatcat:sb5t6r2tnberdd6crdl3pejoke