4 code implementations • 29 Jun 2021 • Yi-Fan Song, Zhang Zhang, Caifeng Shan, Liang Wang
One essential problem in skeleton-based action recognition is how to extract discriminative features over all skeleton joints.
Ranked #17 on Skeleton Based Action Recognition on NTU RGB+D 120
1 code implementation • 20 Oct 2020 • Yi-Fan Song, Zhang Zhang, Caifeng Shan, Liang Wang
However, the complexity of the State-Of-The-Art (SOTA) models of this task tends to be exceedingly sophisticated and over-parameterized, where the low efficiency in model training and inference has obstructed the development in the field, especially for large-scale action datasets.
Ranked #25 on Skeleton Based Action Recognition on NTU RGB+D 120
3 code implementations • 9 Aug 2020 • Yi-Fan Song, Zhang Zhang, Caifeng Shan, Liang Wang
More crucially, on the synthetic occlusion and jittering datasets, the performance deterioration due to the occluded and disturbed joints can be significantly alleviated by utilizing the proposed RA-GCN.
Ranked #43 on Skeleton Based Action Recognition on NTU RGB+D 120
no code implementations • 27 Jun 2020 • Yi-Fan Song, Furkan Elibol, Mengkun She, David Nakath, Kevin Köser
Illuminating a scene with artificial light is a prerequisite for seeing in dark environments.
1 code implementation • 27 Jun 2020 • Yi-Fan Song, David Nakath, Mengkun She, Furkan Elibol, Kevin Köser
Nowadays underwater vision systems are being widely applied in ocean research.
3 code implementations • 16 May 2019 • Yi-Fan Song, Zhang Zhang, Liang Wang
To enhance the robustness of action recognition models to incomplete skeletons, we propose a multi-stream graph convolutional network (GCN) for exploring sufficient discriminative features distributed over all skeleton joints.
Ranked #74 on Skeleton Based Action Recognition on NTU RGB+D
no code implementations • 20 Feb 2019 • Jie Wang, Yi-Fan Song, Tian-Lei Ma
Kernel extreme learning machine (KELM) is a novel feedforward neural network, which is widely used in classification problems.