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Action Shuffle Alternating Learning for Unsupervised Action Segmentation

CVPR 2021 · Video › Action recognition · approach: Temporal action segmentation · 40 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add the action-level embedding learned by action-shuffle SSL (ablation)ASAL · BreakfastF1-score: 35.4 -> 37.9Helped
Add the action-level embedding learned by action-shuffle SSL (ablation)ASAL · BreakfastMoF: 47.7 -> 52.5Helped
Add HMM modeling of action lengths and transitions instead of fixed-transcript Viterbi (ablation)ActionShuffle · BreakfastMoF: 44.1 -> 52.5Helped
Add alternating joint training of the embedding and HMM (ablation)ASAL · BreakfastMoF: 46.8 -> 52.5Helped
Learn a separate action-level embedding for each estimated activity rather than one global embedding (ablation)ASAL · Breakfast, multiple activitiesMoF: 18.3 -> 20.2Helped
Add the action-level embedding instead of using frame-level temporal embedding (ablation)ASAL · Breakfast, multiple activitiesMoF: 17.9 -> 20.2Helped
Add HMM modeling and alternating learning instead of fixed-transcript Viterbi (ablation)ASAL · Breakfast, multiple activitiesMoF: 17.2 -> 20.2Helped
Add alternating joint training rather than keeping the initialized HMM and embedding fixed (ablation)ASAL · Breakfast, multiple activitiesMoF: 18.7 -> 20.2Helped

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