Self-supervised Amodal Video Object Segmentation
Published in NeurIPS, 2022
This work proposes a self-supervised video segmentation framework for inferring complete object shapes in occluded scenes using temporal information.
Recommended citation: Yao, J., Hong, Y., Wang, C., et al. (2022). "Self-supervised Amodal Video Object Segmentation." NeurIPS 2022 Spotlight.
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