Human action recognition from various data modalities: A review
Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …
each action. It has a wide range of applications, and therefore has been attracting increasing …
Constructing stronger and faster baselines for skeleton-based action recognition
One essential problem in skeleton-based action recognition is how to extract discriminative
features over all skeleton joints. However, the complexity of the recent State-Of-The-Art …
features over all skeleton joints. However, the complexity of the recent State-Of-The-Art …
Stronger, faster and more explainable: A graph convolutional baseline for skeleton-based action recognition
One essential problem in skeleton-based action recognition is how to extract discriminative
features over all skeleton joints. However, the complexity of the State-Of-The-Art (SOTA) …
features over all skeleton joints. However, the complexity of the State-Of-The-Art (SOTA) …
Skeleton aware multi-modal sign language recognition
Sign language is commonly used by deaf or speech impaired people to communicate but
requires significant effort to master. Sign Language Recognition (SLR) aims to bridge the …
requires significant effort to master. Sign Language Recognition (SLR) aims to bridge the …
An attention enhanced graph convolutional lstm network for skeleton-based action recognition
Skeleton-based action recognition is an important task that requires the adequate
understanding of movement characteristics of a human action from the given skeleton …
understanding of movement characteristics of a human action from the given skeleton …
Video action transformer network
Abstract We introduce the Action Transformer model for recognizing and localizing human
actions in video clips. We repurpose a Transformer-style architecture to aggregate features …
actions in video clips. We repurpose a Transformer-style architecture to aggregate features …
Dynamic hand gesture recognition using multi-branch attention based graph and general deep learning model
The dynamic hand skeleton data have become increasingly attractive to widely studied for
the recognition of hand gestures that contain 3D coordinates of hand joints. Many …
the recognition of hand gestures that contain 3D coordinates of hand joints. Many …
Vpn: Learning video-pose embedding for activities of daily living
In this paper, we focus on the spatio-temporal aspect of recognizing Activities of Daily Living
(ADL). ADL have two specific properties (i) subtle spatio-temporal patterns and (ii) similar …
(ADL). ADL have two specific properties (i) subtle spatio-temporal patterns and (ii) similar …
Mmnet: A model-based multimodal network for human action recognition in rgb-d videos
Human action recognition (HAR) in RGB-D videos has been widely investigated since the
release of affordable depth sensors. Currently, unimodal approaches (eg, skeleton-based …
release of affordable depth sensors. Currently, unimodal approaches (eg, skeleton-based …
Reciprocal transformations for unsupervised video object segmentation
Unsupervised video object segmentation (UVOS) aims at segmenting the primary objects in
videos without any human intervention. Due to the lack of prior knowledge about the primary …
videos without any human intervention. Due to the lack of prior knowledge about the primary …