[HTML][HTML] A comparison review of transfer learning and self-supervised learning: Definitions, applications, advantages and limitations
Deep learning has emerged as a powerful tool in various domains, revolutionising machine
learning research. However, one persistent challenge is the scarcity of labelled training …
learning research. However, one persistent challenge is the scarcity of labelled training …
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 …
Multi-granularity anchor-contrastive representation learning for semi-supervised skeleton-based action recognition
In the semi-supervised skeleton-based action recognition task, obtaining more
discriminative information from both labeled and unlabeled data is a challenging problem …
discriminative information from both labeled and unlabeled data is a challenging problem …
X-invariant contrastive augmentation and representation learning for semi-supervised skeleton-based action recognition
Semi-supervised skeleton-based action recognition is a challenging problem due to
insufficient labeled data. For addressing this problem, some representative methods …
insufficient labeled data. For addressing this problem, some representative methods …
3mformer: Multi-order multi-mode transformer for skeletal action recognition
Many skeletal action recognition models use GCNs to represent the human body by 3D
body joints connected body parts. GCNs aggregate one-or few-hop graph neighbourhoods …
body joints connected body parts. GCNs aggregate one-or few-hop graph neighbourhoods …
Bayesian generic priors for causal learning.
The article presents a Bayesian model of causal learning that incorporates generic priors--
systematic assumptions about abstract properties of a system of cause-effect relations. The …
systematic assumptions about abstract properties of a system of cause-effect relations. The …
Openhands: Making sign language recognition accessible with pose-based pretrained models across languages
AI technologies for Natural Languages have made tremendous progress recently. However,
commensurate progress has not been made on Sign Languages, in particular, in …
commensurate progress has not been made on Sign Languages, in particular, in …
Geometrymotion-transformer: An end-to-end framework for 3d action recognition
In this work, we propose a new end-to-end optimized two-stream framework called
GeometryMotion-Transformer (GMT) for 3D action recognition. We first observe that the …
GeometryMotion-Transformer (GMT) for 3D action recognition. We first observe that the …
Video-text pre-training with learned regions for retrieval
Video-Text pre-training aims at learning transferable representations from large-scale video-
text pairs via aligning the semantics between visual and textual information. State-of-the-art …
text pairs via aligning the semantics between visual and textual information. State-of-the-art …
Contrastive learning from spatio-temporal mixed skeleton sequences for self-supervised skeleton-based action recognition
Self-supervised skeleton-based action recognition with contrastive learning has attracted
much attention. Recent literature shows that data augmentation and large sets of contrastive …
much attention. Recent literature shows that data augmentation and large sets of contrastive …