MATEC Web Conf.
Volume 277, 20192018 International Joint Conference on Metallurgical and Materials Engineering (JCMME 2018)
|Number of page(s)||5|
|Section||Data and Signal Processing|
|Published online||02 April 2019|
- [Du et al., 2017] Chao Li, Qiaoyong Zhong, Di Xie, Shiliang Pu. Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation, pages 579-583, 2016. [Google Scholar]
- [Girshick et al., 2014] Ross B Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik. Rich feature hierar-chies for accurate object detection and semantic segmentation. CVPR, pages 580-587, 2014. [Google Scholar]
- [He et al., 2016] Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. Deep residual learning for image recog-nition. In CVPR, pages 770-778, 2016. [Google Scholar]
- [Hussein et al., 2013] Mohamed E. Hussein, Marwan Torki, Mohammad A. Gowayyed, and Motaz El-Saban. Human action recognition using a temporal hierarchy of covariance descriptors on 3d joint locations. In IJCAI, pages 639-44, 2013. [Google Scholar]
- [Ji et al., 2014] Yanli Ji, Guo Ye, and Hong Cheng. Inter-active body part contrast mining for human interaction recognition. In ICMEW, pages 1-6, 2014. [Google Scholar]
- [Jin and Choi, 2012] Sou Young Jin and Ho Jin Choi. Essen-tial body-joint and atomic action detection for human ac-tivity recognition using longest common subsequence algorithm. In ICCV, pages 148-159, 2012. [Google Scholar]
- [Ke et al., 2017] Qiuhong Ke, Mohammed Bennamoun, Senjian An, Ferdous Sohel, and Farid Boussaid. A New Representation of Skeleton Sequences for 3D Action Recognition. In CVPR, July 2017. [Google Scholar]
- [Kingma and Ba, 2015] Diederik P Kingma and Jimmy Lei Ba. Adam: A method for stochastic optimization. ICLR, 2015. [Google Scholar]
- [Li et al., 2016] Yanghao Li, Cuiling Lan, Junliang Xing, Wenjun Zeng, Chunfeng Yuan, and Jiaying Liu. On-line human action detection using joint classificationregression recurrent neural networks. ECCV, pages 203-220, 2016. [Google Scholar]
- [Li et al., 2017a] Bo Li, Huahui Chen, Yucheng Chen, Yuchao Dai, and Mingyi He. Skeleton boxes: Solving skeleton based action detection with a single deep convolutional neural network. In ICMEW, pages 613-616, July 2017. [Google Scholar]
- [Li et al., 2017b] Chao Li, Qiaoyong Zhong, Di Xie, and Shiliang Pu. Skeleton-based action recognition with con-volutional neural networks. In ICMEW, pages 597-600, July 2017. [Google Scholar]
- [Liu et al., 2016] Jun Liu, Amir Shahroudy, Dong Xu, and Gang Wang. Spatiotemporal lstm with trust gates for 3d human action recognition. In ECCV, pages 816-833, 2016. [Google Scholar]
- [Liu et al., 2017] Chunhui Liu, Yueyu Hu, Yanghao Li, Si-jie Song, and Jiaying Liu. PKU-MMD: A large scale benchmark for continuous multi-modal human action understanding. ACM Multimedia workshop, 2017. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.