1. Two-Stream Convolutional Networks for Action Recognition in Videos 2. Convolutional Two-Stream Network Fusion for Video Action Recognition 三、基于骨骼关键点的行为识别 1. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition 一、基于 3D CNN 实现的行为识别 1. Learning ...
In this light, we propose GMNet, an action recognition network with global motion representation to fulfill such task. It includes a short-term motion feature extraction module and a motion feature aggregation module. The former one is capable of capturing local motion features from adjacent frames...
ActionRecognitionNet currently does not support INT8 calibration. Copy Copied! # convert 2D RGB model with input sequence length is 32 and input size is 224x224 trtexec --onnx=/path/to/model.onnx \ --maxShapes=input_rgb:16x3x96x224x224 \ --minShapes=input_rgb:1x3x96x224x224 \ -...
T-C3D: Temporal Convolutional 3D Network for Real-time Action Recognition code:tc3d/tc3d Unsupervised Deep Learning of Mid-Level Video Representation for Action Recognition Unsupervised Representation Learning with Long-Term Dynamics for Skeleton Based Action Recognition Deformable Pose Traversal Convolution ...
【论文笔记,action recognition,动作识别】 “Two-Stream Convolutional Networks for Action Recognition in Videos”(2014NIPS) Two Stream方法最初在这篇文章中被提出,基本原理为对视频序列中每两帧计算密集光流,得到密集光流的序列(即temporal信息)。然后对于视频图像(spatial)和密集光流(temporal)分别训练CNN模型,两...
A human action recognition system is affected by many challenges such as background clutter, partial occlusion, lighting, viewpoint, execution rate. Using complementary information from different views can improve view changing and occlusion problems. However, how to effectively integrate the information ...
Q2:对于两个流的卷积网络都是各自训练,然后直接把得到的结果联合,完全独立地得到时间和空间特征会不会忽略了时空之间的联系?(2016CVPR有一篇论文好像是针对这一点的改进,还没看。”Convolutional Two-Stream Network Fusion for Video Action Recognition“(2016CVPR)) ...
Spatial–temporal hypergraph based on dual-stage attention network for multi-view data lightweight action recognition Dual-stage attention network: It includes two stages: Temporal Attention Mechanism based on Trainable Threshold (TAM-TT) and Hypergraph Convolution based o... Z Wu,N Ma,C Wang,.....
1、An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition 作者:Chenyang Si, Wentao Chen, Wei Wang, Liang Wang, Tieniu Tan 论文链接:https://arxiv.org/abs/1902.09130 2、Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal Training...
A review of convolutional-neural-network-based action recognition PRL (2019) Y. Li et al. Large-scale gesture recognition with a fusion of RGB-D data based on optical flow and the C3D model PRL (2019) G. Singh et al. Online real-time multiple spatiotemporal action localisation and predict...