使用onnxruntime部署YOWOv2视频动作检测,包含C++和Python两个版本的程序
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Updated
Mar 28, 2024 - Python
使用onnxruntime部署YOWOv2视频动作检测,包含C++和Python两个版本的程序
Code for the paper "Spot What Matters: Learning Context Using Graph Convolutional Networks for Weakly-Supervised Action Detection"
[CVPR2022] Unsupervised Pre-training for Temporal Action Localization Tasks (UP-TAL)
Detect and count steel mace swings using computer vision
R&D for action detection.
Single run action detector on video stream data
[ECCV 2022] Official Pytorch Implementation of the paper : " Semi-Supervised Temporal Action Detection with Proposal-Free Masking "
This is the official implementation of KORSAL: Key-Point Detection based Online Real-Time Spatio-Temporal Action Detection. We use CenterNet to locate actions spatially - the first use of key-points in action detection.
Annotations for the Mistake Detection benchmark of Assembly101
keep updated on recent advances of Temporal Action Localization
Tensorflow Implementation of the Paper "SST: Single-Stream Temporal Action Proposals" in CVPR 2017.
Action-Net is a dataset containing images of 16 different human actions.
A toolkit for the DeepSportradar Bowl Release challenge. An opportunity to publish at MMSports @ ACMMM and to win 2x $500.
Code for the Paper: Quasi-Online Detection of Take and Release Actions from Egocentric Videos. International Conference on Image Analysis and Processing 2023.
Source code for paper "Multistream Temporal Convolutional Network for Correct/Incorrect Patient Transfer Action Detection Using Body Sensor Network" on public dataset C-MHAD
[IJCV] AOE-Net: Entities Interactions Modeling with Adaptive Attention Mechanism for Temporal Action Proposals Generation
This is an official implementation of TubeR: Tubelet Transformer for Video Action Detection Supplementary Material
A curated list of papers in the domain of spatio-temporal action detection (or action localization.) NOTE: This repository does not contains papers for Temporal Action Localization.
Code and material relevant to the paper, "Introducing SSBD+ Dataset with a Convolutional Pipeline for detecting Self-Stimulatory Behaviours in Children using raw videos"
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