A survey on 3d skeleton-based action recognition using learning method

B Ren, M Liu, R Ding, H Liu - Cyborg and Bionic Systems, 2024 - spj.science.org
Three-dimensional skeleton-based action recognition (3D SAR) has gained important
attention within the computer vision community, owing to the inherent advantages offered by …

Transformer for skeleton-based action recognition: A review of recent advances

W **n, R Liu, Y Liu, Y Chen, W Yu, Q Miao - Neurocomputing, 2023 - Elsevier
Skeleton-based action recognition has rapidly become one of the most popular and
essential research topics in computer vision. The task is to analyze the characteristics of …

Mhformer: Multi-hypothesis transformer for 3d human pose estimation

W Li, H Liu, H Tang, P Wang… - Proceedings of the …, 2022 - openaccess.thecvf.com
Estimating 3D human poses from monocular videos is a challenging task due to depth
ambiguity and self-occlusion. Most existing works attempt to solve both issues by exploiting …

Mixste: Seq2seq mixed spatio-temporal encoder for 3d human pose estimation in video

J Zhang, Z Tu, J Yang, Y Chen… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
Recent transformer-based solutions have been introduced to estimate 3D human pose from
2D keypoint sequence by considering body joints among all frames globally to learn spatio …

Learning discriminative representations for skeleton based action recognition

H Zhou, Q Liu, Y Wang - … of the IEEE/CVF Conference on …, 2023 - openaccess.thecvf.com
Human action recognition aims at classifying the category of human action from a segment
of a video. Recently, people have dived into designing GCN-based models to extract …

Star-transformer: a spatio-temporal cross attention transformer for human action recognition

D Ahn, S Kim, H Hong, BC Ko - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
In action recognition, although the combination of spatio-temporal videos and skeleton
features can improve the recognition performance, a separate model and balancing feature …

P-stmo: Pre-trained spatial temporal many-to-one model for 3d human pose estimation

W Shan, Z Liu, X Zhang, S Wang, S Ma… - European Conference on …, 2022 - Springer
This paper introduces a novel Pre-trained Spatial Temporal Many-to-One (P-STMO) model
for 2D-to-3D human pose estimation task. To reduce the difficulty of capturing spatial and …

Gfpose: Learning 3d human pose prior with gradient fields

H Ci, M Wu, W Zhu, X Ma, H Dong… - Proceedings of the …, 2023 - openaccess.thecvf.com
Learning 3D human pose prior is essential to human-centered AI. Here, we present GFPose,
a versatile framework to model plausible 3D human poses for various applications. At the …

Humansd: A native skeleton-guided diffusion model for human image generation

X Ju, A Zeng, C Zhao, J Wang… - Proceedings of the …, 2023 - openaccess.thecvf.com
Controllable human image generation (HIG) has attracted significant attention from
academia and industry for its numerous real-life applications. State-of-the-art solutions, such …

Gla-gcn: Global-local adaptive graph convolutional network for 3d human pose estimation from monocular video

BXB Yu, Z Zhang, Y Liu, S Zhong… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract 3D human pose estimation has been researched for decades with promising fruits.
3D human pose lifting is one of the promising research directions toward the task where …