Transformer for skeleton-based action recognition: A review of recent advances
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 …
essential research topics in computer vision. The task is to analyze the characteristics of …
Deep contrastive representation learning with self-distillation
Recently, contrastive learning (CL) is a promising way of learning discriminative
representations from time series data. In the representation hierarchy, semantic information …
representations from time series data. In the representation hierarchy, semantic information …
On the use of deep learning for video classification
The video classification task has gained significant success in the recent years. Specifically,
the topic has gained more attention after the emergence of deep learning models as a …
the topic has gained more attention after the emergence of deep learning models as a …
Pyramid self-attention polymerization learning for semi-supervised skeleton-based action recognition
Most semi-supervised skeleton-based action recognition approaches aim to learn the
skeleton action representations only at the joint level, but neglect the crucial motion …
skeleton action representations only at the joint level, but neglect the crucial motion …
Dynamic dense graph convolutional network for skeleton-based human motion prediction
Graph Convolutional Networks (GCN) which typically follows a neural message passing
framework to model dependencies among skeletal joints has achieved high success in …
framework to model dependencies among skeletal joints has achieved high success in …
Self-supervised graph-level representation learning with adversarial contrastive learning
The recently developed unsupervised graph representation learning approaches apply
contrastive learning into graph-structured data and achieve promising performance …
contrastive learning into graph-structured data and achieve promising performance …
TranSkeleton: Hierarchical spatial–temporal transformer for skeleton-based action recognition
In skeleton-based action recognition, it has been a dominant paradigm to extract motion
features with temporal convolution and model spatial correlations with graph convolution …
features with temporal convolution and model spatial correlations with graph convolution …
Neighbor-guided consistent and contrastive learning for semi-supervised action recognition
Semi-supervised learning has been well established in the area of image classification but
remains to be explored in video-based action recognition. FixMatch is a state-of-the-art semi …
remains to be explored in video-based action recognition. FixMatch is a state-of-the-art semi …
Msvit: training multiscale vision transformers for image retrieval
The recently developed vision transformer (ViT) has achieved promising results on image
retrieval compared to convolutional neural networks. However, most of these vision …
retrieval compared to convolutional neural networks. However, most of these vision …
Skeleton-based action recognition with select-assemble-normalize graph convolutional networks
H Tian, X Ma, X Li, Y Li - IEEE Transactions on Multimedia, 2023 - ieeexplore.ieee.org
Skeleton-based action recognition has been substantially driven by the development of
artificial intelligence technology and deep sensors. Recently, graph convolutional networks …
artificial intelligence technology and deep sensors. Recently, graph convolutional networks …