SOTAVerified

Weakly Supervised Action Localization

In this task, the training data consists of videos with a list of activities in them without any temporal boundary annotations. However, while testing, given a video, the algorithm should recognize the activities in the video and also provide the start and end time.

Papers

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Showing 1–10 of 55 papers

TitleStatusHype
Multilevel semantic and adaptive actionness learning for weakly supervised temporal action localizationCode0
Weakly supervised temporal action localization with actionness-guided false positive suppressionCode0
Revisiting Foreground and Background Separation in Weakly-supervised Temporal Action Localization: A Clustering-based ApproachCode1
Is Weakly-supervised Action Segmentation Ready For Human-Robot Interaction? No, Let's Improve It With Action-union LearningCode2
POTLoc: Pseudo-Label Oriented Transformer for Point-Supervised Temporal Action Localization—0
HR-Pro: Point-supervised Temporal Action Localization via Hierarchical Reliability PropagationCode1
Weakly-Supervised Action Localization by Hierarchically-structured Latent Attention Modeling—0
Actionness Inconsistency-guided Contrastive Learning for Weakly-supervised Temporal Action LocalizationCode1
Proposal-Based Multiple Instance Learning for Weakly-Supervised Temporal Action LocalizationCode1
Two-Stream Networks for Weakly-Supervised Temporal Action Localization With Semantic-Aware Mechanisms—0
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All datasetsTHUMOS 2014THUMOS14ActivityNet-1.2ActivityNet-1.3GTEABEOIDFineActionTHUMOS' 14

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AU-Action[email protected]:0.776.9—Unverified
2HR-Pro[email protected]:0.747.3—Unverified
3LACP[email protected]:0.743.5—Unverified
4Li et al.[email protected]:0.736.4—Unverified
5Ju et al.[email protected]:0.733.7—Unverified
6SF-Net[email protected]:0.731—Unverified