A review of video action recognition based on 3D convolution
X Huang, Z Cai - Computers and Electrical Engineering, 2023 - Elsevier
Video action recognition is one of the topics for video understanding. Over the past decade,
video action recognition has made great progress due to the emergence of deep learning …
video action recognition has made great progress due to the emergence of deep learning …
Cee-net: complementary end-to-end network for 3d human pose generation and estimation
The limited number of actors and actions in existing datasets make 3D pose estimators tend
to overfit, which can be seen from the performance degradation of the algorithm on cross …
to overfit, which can be seen from the performance degradation of the algorithm on cross …
Enhancing traffic safety with parallel dense video captioning for end-to-end event analysis
This paper introduces our solution for Track 2 in AI City Challenge 2024. The task aims to
solve traffic safety description and analysis with the dataset of Woven Traffic Safety (WTS) a …
solve traffic safety description and analysis with the dataset of Woven Traffic Safety (WTS) a …
Glimpse and focus: Global and local-scale graph convolution network for skeleton-based action recognition
In the 3D skeleton-based action recognition task, learning rich spatial and temporal motion
patterns from body joints are two foundational yet under-explored problems. In this paper …
patterns from body joints are two foundational yet under-explored problems. In this paper …
Spatial–temporal hypergraph based on dual-stage attention network for multi-view data lightweight action recognition
For the problems of irrelevant frames and high model complexity in action recognition, we
propose a Spatial–Temporal Hypergraph based on Dual-Stage Attention Network (STHG …
propose a Spatial–Temporal Hypergraph based on Dual-Stage Attention Network (STHG …
Boosting Rare Scenario Perception in Autonomous Driving: An Adaptive Approach With MoEs and LoRA
Autonomous driving technology has achieved remarkable advancements, offering
substantial potential to revolutionize traffic safety and smart mobility. However, when faced …
substantial potential to revolutionize traffic safety and smart mobility. However, when faced …
Learning heterogeneous spatial–temporal context for skeleton-based action recognition
Graph convolution networks (GCNs) have been widely used and achieved fruitful progress
in the skeleton-based action recognition task. In GCNs, node interaction modeling …
in the skeleton-based action recognition task. In GCNs, node interaction modeling …
Pedestrian crossing intention prediction from surveillance videos for over-the-horizon safety warning
Pedestrian crossing intention prediction could effectively prevent traffic injuries and improve
pedestrian safety. This paper focuses on pedestrian crossing intention prediction from …
pedestrian safety. This paper focuses on pedestrian crossing intention prediction from …
FineSports: A Multi-person Hierarchical Sports Video Dataset for Fine-grained Action Understanding
Fine-grained action analysis in multi-person sports is complex due to athletes' quick
movements and intense physical confrontations which result in severe visual obstructions in …
movements and intense physical confrontations which result in severe visual obstructions in …
Blockchain-based Vision Transformer Network for Safe Driving Perception
Driver distraction is a principal cause of traffic accidents. In a study conducted by the
National Highway Traffic Safety Administration, engaging in activities such as interacting …
National Highway Traffic Safety Administration, engaging in activities such as interacting …