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Boundary-aware Self-supervised Learning for Video Scene Segmentation. (arXiv:2201.05277v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
Self-supervised learning has drawn attention through its effectiveness in
learning in-domain representations with no ground-truth annotations; in
particular, it is shown that properly designed pretext tasks (e.g., contrastive
prediction task) bring significant performance gains for downstream tasks
(e.g., classification task). Inspired from this, we tackle video scene
segmentation, which is a task of temporally localizing scene boundaries in a
video, with a self-supervised learning framework where we mainly focus on
designing effective pretext tasks. In our framework, we discover a …
arxiv cv learning segmentation self-supervised learning supervised learning video