Action Behavior Learning Based on a New Multi-Scale Interactive Perception Network

Action Behavior Learning Based on a New Multi-Scale Interactive Perception Network

Action recognition is a fundamental research topic in the field of video understanding, but classical action recognition relies on a large amount of manually annotated video data, which limits its development. Small sample action recognition is a promising topic that can overcome the dependence on l...

Bibliografski detalji
Glavni autori:	Chunlin Zheng, Jun Gu, Sheng Xu
Format:	Članak
Jezik:	English
Izdano:	IEEE 2023-01-01
Serija:	IEEE Access
Teme:	Action recognition small sample learning video understanding meta learning
Online pristup:	https://ieeexplore.ieee.org/document/10352162/

Slični predmeti

Short Video Behavior Recognition Combining Scene and Behavior Features
od: DONG Xu, TAN Li, ZHOU Lina, SONG Yanyan
Izdano: (2020-10-01)

Multi-Modal Human Action Segmentation Using Skeletal Video Ensembles
od: James Dickens, i dr.
Izdano: (2023-11-01)

A Novel Spatio-Temporal-Wise Network for Action Recognition
od: Zhengbao Cai
Izdano: (2023-01-01)

Hybrid attentive prototypical network for few-shot action recognition
od: Zanxi Ruan, i dr.
Izdano: (2024-08-01)

Multi-Stream Single Network: Efficient Compressed Video Action Recognition With a Single Multi-Input Multi-Output Network
od: Hayato Terao, i dr.
Izdano: (2024-01-01)

LGANet: Local and global attention are both you need for action recognition
od: Hao Wang, i dr.
Izdano: (2023-10-01)

Extensible Hierarchical Method of Detecting Interactive Actions for Video Understanding
od: Jinyoung Moon, i dr.
Izdano: (2017-08-01)

Dynamic Equilibrium Module for Action Recognition
od: Qili Zeng, i dr.
Izdano: (2021-01-01)

LaM-2SRN: A Method Which Can Enhance Local Features and Detect Moving Objects for Action Recognition
od: Yangyang Qiao, i dr.
Izdano: (2020-01-01)

Audio-Visual Action Recognition Using Transformer Fusion Network
od: Jun-Hwa Kim, i dr.
Izdano: (2024-01-01)

Variable Temporal Length Training for Action Recognition CNNs
od: Tan-Kun Li, i dr.
Izdano: (2024-05-01)

Meta‐action descriptor for action recognition in RGBD video
od: Min Huang, i dr.
Izdano: (2017-06-01)

Action Recognition in Videos through a Transfer-Learning-Based Technique
od: Elizabeth López-Lozada, i dr.
Izdano: (2024-10-01)

A Multi-Scale Video Longformer Network for Action Recognition
od: Congping Chen, i dr.
Izdano: (2024-01-01)

Mutual modality learning for video action classification
od: S.A. Komkov, i dr.
Izdano: (2023-08-01)

Compressed video ensemble based pseudo-labeling for semi-supervised action recognition
od: Hayato Terao, i dr.
Izdano: (2022-09-01)

Temporal Memory Network Towards Real-Time Video Understanding
od: Ziming Liu, i dr.
Izdano: (2020-01-01)

Video Action Understanding
od: Matthew S. Hutchinson, i dr.
Izdano: (2021-01-01)

Study on video action recognition based on augment negative example multi-granularity discrimination model
od: LIU Liangzhen, i dr.
Izdano: (2024-12-01)

An Overview of the Vision-Based Human Action Recognition Field
od: Fernando Camarena, i dr.
Izdano: (2023-04-01)

TEDdet: Temporal Feature Exchange and Difference Network for Online Real-Time Action Detection
od: Yu Liu, i dr.
Izdano: (2022-01-01)

Non-Local Temporal Difference Network for Temporal Action Detection
od: Yilong He, i dr.
Izdano: (2022-11-01)

Action Progression Networks for Temporal Action Detection in Videos
od: Chong-Kai Lu, i dr.
Izdano: (2024-01-01)

Spatiotemporal Interaction Residual Networks with Pseudo3D for Video Action Recognition
od: Jianyu Chen, i dr.
Izdano: (2020-06-01)

Unsupervised Action Proposals Using Support Vector Classifiers for Online Video Processing
od: Marcos Baptista Ríos, i dr.
Izdano: (2020-05-01)

EMO-MoviNet: Enhancing Action Recognition in Videos with EvoNorm, Mish Activation, and Optimal Frame Selection for Efficient Mobile Deployment
od: Tarique Hussain, i dr.
Izdano: (2023-09-01)

Interpretable Information Visualization for Enhanced Temporal Action Detection in Videos
od: Dasom Ahn, i dr.
Izdano: (2024-01-01)

Disentangling rodent behaviors to improve automated behavior recognition
od: Elsbeth A. Van Dam, i dr.
Izdano: (2023-07-01)

Fusion of Video and Inertial Sensing for Deep Learning–Based Human Action Recognition
od: Haoran Wei, i dr.
Izdano: (2019-08-01)

Survey on deep learning methods in human action recognition
od: Maryam Koohzadi, i dr.
Izdano: (2017-12-01)

Using Action Research and Action Learning (ARAL) to develop a response to the abuse of older people in a healthcare context
od: Fiona McAlinden
Izdano: (2015-10-01)

Intelligent Human–UAV Interaction System with Joint Cross-Validation over Action–Gesture Recognition and Scene Understanding
od: Bo Chen, i dr.
Izdano: (2019-08-01)

Robust Feature-Based Automated Multi-View Human Action Recognition System
od: Kuang-Pen Chou, i dr.
Izdano: (2018-01-01)

Multi-scale Gated Graph Convolutional Network for Skeleton-based Action Recognition
od: GAN Chuang, WU Gui-xing, ZHAN Qing-yuan, WANG Peng-kun, PENG Zhi-lei
Izdano: (2022-01-01)

Improving the Ability of Students' Understanding Through Videos at PIAUD Study Program UIN Fatmawati Sukarno Bengkulu/ Peningkatan Kemampuan Pemahaman Mahasiswa Melalui Video pada Program Studi PIAUD UIN Fatmawati Sukarno Bengkulu
od: Indah Maysela Azzahra, i dr.
Izdano: (2022-08-01)

Multi‐cue combination network for action‐based video classification
od: Yan Tian, i dr.
Izdano: (2019-09-01)

Tencent AVS: A Holistic Ads Video Dataset for Multi-Modal Scene Segmentation
od: Jie Jiang, i dr.
Izdano: (2022-01-01)

A Multi-Scale Feature Attention Image Recognition Algorithm
od: Xin MingYuan, i dr.
Izdano: (2023-09-01)

A Channel-Wise Spatial-Temporal Aggregation Network for Action Recognition
od: Huafeng Wang, i dr.
Izdano: (2021-12-01)

Skeletal Keypoint-Based Transformer Model for Human Action Recognition in Aerial Videos
od: Shahab Uddin, i dr.
Izdano: (2024-01-01)