Papers › Self-Supervised Learning for Semi-Supervised Temporal Action Proposal

Self-Supervised Learning for Semi-Supervised Temporal Action Proposal

7 Apr 2021CVPR 2021 1arXiv:2104.03214archive 2025-07-28

Xiang Wang, Shiwei Zhang, Zhiwu Qing, Yuanjie Shao, Changxin Gao, Nong Sang

Self-supervised learning presents a remarkable performance to utilize unlabeled data for various video tasks. In this paper, we focus on applying the power of self-supervised methods to improve semi-supervised action proposal generation. Particularly, we design an effective Self-supervised Semi-supervised Temporal Action Proposal (SSTAP) framework. The SSTAP contains two crucial branches, i.e., temporal-aware semi-supervised branch and relation-aware self-supervised branch. The semi-supervised branch improves the proposal model by introducing two temporal perturbations, i.e., temporal feature shift and temporal feature flip, in the mean teacher framework. The self-supervised branch defines two pretext tasks, including masked feature reconstruction and clip-order prediction, to learn the relation of temporal clues. By this means, SSTAP can better explore unlabeled videos, and improve the discriminative abilities of learned action features. We extensively evaluate the proposed SSTAP on THUMOS14 and ActivityNet v1.3 datasets. The experimental results demonstrate that SSTAP significantly outperforms state-of-the-art semi-supervised methods and even matches fully-supervised methods. Code is available at https://github.com/wangxiang1230/SSTAP.

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Tasks

Self-Supervised LearningSemi-Supervised Action DetectionTemporal Action Localization

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Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Temporal Action Localization ActivityNet-1.3 SSTAP@100%+ mAP 34.48 #25 of 33 Archive leaderboard report
Temporal Action Localization ActivityNet-1.3 SSTAP@100%+ mAP IOU@0.5 50.72 #25 of 33 Archive leaderboard report
Temporal Action Localization ActivityNet-1.3 SSTAP@100%+ mAP IOU@0.75 35.28 #25 of 33 Archive leaderboard report
Temporal Action Localization ActivityNet-1.3 SSTAP@100%+ mAP IOU@0.95 7.87 #25 of 33 Archive leaderboard report

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