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Distillation of Human-Object Interaction Contexts for Action Recognition
[article]
2021
arXiv
pre-print
Modeling spatial-temporal relations is imperative for recognizing human actions, especially when a human is interacting with objects, while multiple objects appear around the human differently over time. Most existing action recognition models focus on learning overall visual cues of a scene but disregard informative fine-grained features, which can be captured by learning human-object relationships and interactions. In this paper, we learn human-object relationships by exploiting the
arXiv:2112.09448v1
fatcat:tqjx6nyuvvhrzmyfifvsx56gde