Few-Shot Temporal Action Localization (FS-TAL) aims to detect human actions in untrimmed videos using a limited number of training samples. Existing FS-TAL ...
Chen, G., Zheng, Y.-D., Wang, L., & Lu, T. (2022). DCAN: Improving temporal action detection via dual context aggregation. Vol. 36, In Proc. AAAI conf. artif.
CGCN: Context graph convolutional network for few-shot temporal action localization. S Zhang, H Wang, L Wang, X Han, Q Tian. Information Processing & Management ...
The present few-shot temporal action localization model can't handle the situation where videos contain multiple action instances. So the purpose of this ...
Missing: CGCN: | Show results with:CGCN:
Dec 1, 2021 · Upon the graph we built, we then apply graph convolutional networks (GCNs) to model the relations among different action units, which is able to ...
Missing: CGCN: | Show results with:CGCN:
Sep 30, 2022 · In this paper, we claim that the relations between action units play an important role in action localization, and a more powerful action ...
Missing: CGCN: | Show results with:CGCN:
Upon the graph we built, we then apply graph convolutional networks (GCNs) to model the relations among different action units, which is able to learn more ...
CGCN: Context graph convolutional network for few-shot temporal action localization · Dynamically Adaptive Deformable Feature Fusion for multi-scale character ...
CGCN: Context graph convolutional network for few-shot temporal action localization ... graph convolutional network for few-shot temporal action localization ...
Schematic of our P-GCN model. Given a set of proposals from the input untrimmed video, we instantiate the nodes in the graph by each proposal. Then, edges are ...
Missing: few- | Show results with:few-