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cs.CV2023
DEVIAS: Learning Disentangled Video Representations of Action and Scene
Kyungho Bae, Geo Ahn, Youngrae Kim +1
Video recognition models often learn scene-biased action representation due to the spurious correlation between actions and scenes in the training data. Such models show poor perfo…
cs.CV2023
GLAD: Global-Local View Alignment and Background Debiasing for Unsupervised Video Domain Adaptation with Large Domain Gap
Hyogun Lee, Kyungho Bae, Seong Jong Ha +3
In this work, we tackle the challenging problem of unsupervised video domain adaptation (UVDA) for action recognition. We specifically focus on scenarios with a substantial domain…