Feichtenhofer C, Pinz A, Zisserman A (2016) Convolutional two-stream network fusion for video action recognition. In: Proceedings of IEEE computer society conference on computer vision and pattern recognition, vol 2016-Decem, no. i, pp. 1933–1941, 2016. https://doi.org/10.1109/CVPR.2016.21...
A New Representation of Skeleton Sequences for 3D Action Recognition CVPR2017 骨架动作识别, 参考博客,本文的主要思想是将3d骨架坐标转换成图片,然后再用卷积网络提取特征,时域上的特征通过特殊的卷积核来提取,以达到时序记忆的目的。 Investigation of Different Skeleton Features for CNN-based 3D Action Recognitio...
Action recognition by dense trajectories. In 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) https://doi.org/10.1109/cvpr.2011.5995407 (IEEE, 2011). Liu, J. & Shah, M. Learning human actions via information maximization. In 2008 IEEE Conference on Computer...
《3D Convolutional Neural Networks for Human Action Recognition》论文阅读笔记,程序员大本营,技术文章内容聚合第一站。
on Computer Vision and Pattern Recognition Workshops.S. Cherla, K. Kulkarni, A. Kale, and V. Ramasubramanian, "Towards fast, view-invariant human action recognition," in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR '08), pp. 1-8, June 2008....
浅谈对Two-Stream 3D Convolutional Neural Network for Human Skeleton-Based Action Recognition,基于人体骨架的动作识,程序员大本营,技术文章内容聚合第一站。
发表期刊/会议:Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 影响因子/会议级别:A会(顶会) 论文网址:CVPR 2022 Open Access Repository 研究动机 论文旨在解决人类骨架动作识别问题,通过图卷积网络(GCN)来处理复杂的人体行为关系。虽然现有方法已经对骨架编码进行了研究,但很少有...
This is the implementation of CVPR2020 paper “Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition”. - microsoft/SGN
action recognition motivation Both recurrent and convolutional operations are neighborhood-based local operations either in space or time; hence local-range information is repeatedly extracted and propagated to capture long-range dependencies. Many works have designed networks with hierarchical structure to ob...
Human Action Recognition (HAR) involves human activity monitoring task in different areas of medical, education, entertainment, visual surveillance, video