Jan 30, 2023 · For the sake of improving the recognition accuracy on occluded skeleton data, we put forward an occlusion-aware multistream fusion graph convolutional network.
The pioneering work on graph convolution-based skeleton action recognition is the spatial-temporal graph convolutional network (ST-. GCN) proposed by Yan et al.
An occluded part-aware graph convolutional network (OP-GCN) to address the challenge of action recognition in occlusion situations using the optimal occluded ...
Oct 22, 2024 · For the sake of improving the recognition accuracy on occluded skeleton data, we put forward an occlusion-aware multi-stream fusion graph ...
Occluded Part-aware Graph Convolutional Networks for Skeleton-based Action Recognition (OP-GCN) ... However, action recognition in occlusion situations ...
Missing: Neural | Show results with:Neural
Aug 11, 2024 · Occlusion-Aware Graph Neural Networks for Skeleton Action Recognition. Article. Oct 2023. Wuzhen Shi · Dan Li · Yang Wen · Wu ...
Symbiotic Graph Neural Networks for 3D Skeleton-based Human Action Recognition and Motion Prediction. 2019. 43. ST-GCN [Vanilla, 2D Skeleton]. 90.1, 95.1.
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What is skeleton-based action recognition?
Oct 27, 2023 · This paper addresses occluded and noise-robust skeleton-based action recognition and presents a novel Dual Inhibition Training strategy.
FRD trains a lightweight recognition neural network structure that can be quickly executed at a low computational cost.
Skeleton-based Action Recognition is a computer vision task that involves recognizing human actions from a sequence of 3D skeletal joint data.