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Found 3 papers, 2 papers with code
Revisiting Foreground and Background Separation in Weakly-supervised Temporal Action Localization: A Clustering-based Approach
It comprises two core components: a snippet clustering component that groups the snippets into multiple latent clusters and a cluster classification component that further classifies the cluster as foreground or background.
Improve Temporal Action Proposals using Hierarchical Context
In this paper, we propose a novel hierarchical context network (HCN) to further explore the snippet-level and proposal-level contexts, which are used to improve the representations of snippets and proposals, respectively.
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Temporal Action Proposal Generation
on THUMOS' 14
Boundary-Enhanced Co-Training for Weakly Supervised Semantic Segmentation
The existing weakly supervised semantic segmentation (WSSS) methods pay much attention to generating accurate and complete class activation maps (CAMs) as pseudo-labels, while ignoring the importance of training the segmentation networks.
