TP-LSM: visual temporal pyramidal time modeling network to multi-label action detection in image-based AI
Open Access
- 30 August 2024
- journal article
- research article
- Published by Springer Nature in The Visual Computer
- Vol. 41 (5) , 3263-3281
Abstract
No abstract availableKeywords
Funding Information
- National Key Research and Development Program of China (No.2022YFB3305803, No.2022YFB3305803)
This publication has 63 references indexed in Scilit:
- Multi‐temporal scale aggregation refinement graph convolutional network for skeleton‐based action recognitionComputer Animation and Virtual Worlds, 2023
- CHAN: Skeleton based action recognition by multi‐level feature learningComputer Animation and Virtual Worlds, 2023
- Bidirectional temporal feature for 3D human pose and shape estimation from a videoComputer Animation and Virtual Worlds, 2023
- Distillation of human–object interaction contexts for action recognitionComputer Animation and Virtual Worlds, 2022
- AeS‐GCN: Attention‐enhanced semantic‐guided graph convolutional networks for skeleton‐based action recognitionComputer Animation and Virtual Worlds, 2022
- Parallel‐branch network for 3D human pose and shape estimation in videoComputer Animation and Virtual Worlds, 2022
- SF-Net: Single-Frame Supervision for Temporal Action Localization2020
- Densely connected GCN model for motion predictionComputer Animation and Virtual Worlds, 2020
- Hybrid features for skeleton‐based action recognition based on network fusionComputer Animation and Virtual Worlds, 2020
- BSN: Boundary Sensitive Network for Temporal Action Proposal Generation2018