Self-Supervised Temporal Domain Adaptation

Introduced by Chen et al. in Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation

Self-Supervised Temporal Domain Adaptation (SSTDA) is a method for action segmentation with self-supervised temporal domain adaptation. It contains two self-supervised auxiliary tasks (binary and sequential domain prediction) to jointly align cross-domain feature spaces embedded with local and global temporal dynamics.

Source: Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation

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Papers

Paper	Code	Results	Date	Stars

Tasks

Task	Papers	Share
Action Segmentation	2	66.67%
Domain Adaptation	1	33.33%

Usage Over Time

This feature is experimental; we are continuously improving our matching algorithm.

Components

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Categories

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Domain Adaptation