Weakly Supervised Temporal Action Localization
31 papers with code • 1 benchmarks • 2 datasets
Libraries
Use these libraries to find Weakly Supervised Temporal Action Localization models and implementations
THUMOS14
FineAction
Latest papers
Weakly Supervised Temporal Action Localization via Representative Snippet Knowledge Propagation
Our method seeks to mine the representative snippets in each video for propagating information between video snippets to generate better pseudo labels.
ACGNet: Action Complement Graph Network for Weakly-supervised Temporal Action Localization
xjtupanda/ACGNet
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Weakly-supervised temporal action localization (WTAL) in untrimmed videos has emerged as a practical but challenging task since only video-level labels are available.
Background-Click Supervision for Temporal Action Localization
vividle/backtal
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Weakly supervised temporal action localization aims at learning the instance-level action pattern from the video-level labels, where a significant challenge is action-context confusion.
Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization
In this paper, we present a framework named FAC-Net based on the I3D backbone, on which three branches are appended, named class-wise foreground classification branch, class-agnostic attention branch and multiple instance learning branch.
Learning Action Completeness from Points for Weakly-supervised Temporal Action Localization
Pilhyeon/Learning-Action-Completeness-from-Points
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ICCV 2021
To learn completeness from the obtained sequence, we introduce two novel losses that contrast action instances with background ones in terms of action score and feature similarity, respectively.
Cross-modal Consensus Network forWeakly Supervised Temporal Action Localization
harlanhong/MM2021-CO2-Net
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Proceedings of the 29th ACM International Conference on Multimedia 2021
In this work, we argue that the features extracted from the pretrained extractor, e. g., I3D, are not the WS-TALtask-specific features, thus the feature re-calibration is needed for reducing the task-irrelevant information redundancy.
Cross-modal Consensus Network for Weakly Supervised Temporal Action Localization
In this work, we argue that the features extracted from the pretrained extractor, e. g., I3D, are not the WS-TALtask-specific features, thus the feature re-calibration is needed for reducing the task-irrelevant information redundancy.
ACM-Net: Action Context Modeling Network for Weakly-Supervised Temporal Action Localization
ispc-lab/ACM-Net
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Traditional methods mainly focus on foreground and background frames separation with only a single attention branch and class activation sequence.
CoLA: Weakly-Supervised Temporal Action Localization with Snippet Contrastive Learning
In this paper, we argue that learning by comparing helps identify these hard snippets and we propose to utilize snippet Contrastive learning to Localize Actions, CoLA for short.
The Blessings of Unlabeled Background in Untrimmed Videos
The key challenge is how to distinguish the action of interest segments from the background, which is unlabelled even on the video-level.
