暂无分享,去创建一个
Nanxuan Zhao | Ailing Zeng | Lei Yang | Qiang Xu | Minhao Liu | Xiao Sun | Xiao Sun | Lei Yang | Ailing Zeng | Nanxuan Zhao | Qiang Xu | Minhao Liu
[1] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[2] Xiaopeng Hong,et al. Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching , 2019, AAAI.
[3] Ken-ichi Kawarabayashi,et al. Representation Learning on Graphs with Jumping Knowledge Networks , 2018, ICML.
[4] James J. Little,et al. Exploiting Temporal Information for 3D Human Pose Estimation , 2017, ECCV.
[5] Dahua Lin,et al. Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition , 2018, AAAI.
[6] Louahdi Khoudour,et al. A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera , 2019, Sensors.
[7] Gang Yu,et al. Cascaded Pyramid Network for Multi-person Pose Estimation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[8] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[9] Wei Tang,et al. Learning Global Pose Features in Graph Convolutional Networks for 3D Human Pose Estimation , 2020, ACCV.
[10] Xiaoxiao Li,et al. Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[11] Dong Liu,et al. Deep High-Resolution Representation Learning for Human Pose Estimation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Haiping Lu,et al. Hop-Hop Relation-aware Graph Neural Networks , 2020, ArXiv.
[13] Pascal Fua,et al. Monocular 3D Human Pose Estimation in the Wild Using Improved CNN Supervision , 2016, 2017 International Conference on 3D Vision (3DV).
[14] Kaiming He,et al. Focal Loss for Dense Object Detection , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[15] Xu Chen,et al. Actional-Structural Graph Convolutional Networks for Skeleton-Based Action Recognition , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Matteo Matteucci,et al. Spatial Temporal Transformer Network for Skeleton-based Action Recognition , 2020, ICPR Workshops.
[17] Yifan Zhang,et al. Decoupling GCN with DropGraph Module for Skeleton-Based Action Recognition , 2020, ECCV.
[18] Nojun Kwak,et al. 3D Human Pose Estimation with Relational Networks , 2018, BMVC.
[19] Le Wang,et al. High-order Graph Convolutional Networks for 3D Human Pose Estimation , 2020, BMVC.
[20] David Picard,et al. 2D/3D Pose Estimation and Action Recognition Using Multitask Deep Learning , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[21] Dario Pavllo,et al. 3D Human Pose Estimation in Video With Temporal Convolutions and Semi-Supervised Training , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Jingang Shi,et al. Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition , 2020, ACM Multimedia.
[23] Gim Hee Lee,et al. Trajectory Space Factorization for Deep Video-Based 3D Human Pose Estimation , 2019, BMVC.
[24] Gang Wang,et al. NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Nanning Zheng,et al. Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Cristian Sminchisescu,et al. Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Gang Wang,et al. NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[28] Yizhou Wang,et al. Optimizing Network Structure for 3D Human Pose Estimation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[29] Yongjun Xu,et al. Rethinking the Number of Channels for the Convolutional Neural Network , 2019, ArXiv.
[30] Song-Chun Zhu,et al. Learning Pose Grammar to Encode Human Body Configuration for 3D Pose Estimation , 2017, AAAI.
[31] James J. Little,et al. A Simple Yet Effective Baseline for 3d Human Pose Estimation , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[32] Ruiyuan Gao,et al. Hop-Aware Dimension Optimization for Graph Neural Networks , 2021, ArXiv.
[33] Kristina Lerman,et al. MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing , 2019, ICML.
[34] Yan Chen,et al. Generalizing Monocular 3D Human Pose Estimation in the Wild , 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).
[35] Haitao Lin,et al. LookHops: light multi-order convolution and pooling for graph classification , 2020, ArXiv.
[36] Stephen Lin,et al. SRNet: Improving Generalization in 3D Human Pose Estimation with a Split-and-Recombine Approach , 2020, ECCV.
[37] Bernard Ghanem,et al. DeepGCNs: Can GCNs Go As Deep As CNNs? , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[38] Sanghoon Lee,et al. Propagating LSTM: 3D Pose Estimation Based on Joint Interdependency , 2018, ECCV.
[39] Yu Tian,et al. Semantic Graph Convolutional Networks for 3D Human Pose Regression , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Zhenghao Chen,et al. Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[41] Nadia Magnenat-Thalmann,et al. Exploiting Spatial-Temporal Relationships for 3D Pose Estimation via Graph Convolutional Networks , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[42] Alan L. Yuille,et al. OriNet: A Fully Convolutional Network for 3D Human Pose Estimation , 2018, BMVC.
[43] Jia Deng,et al. Stacked Hourglass Networks for Human Pose Estimation , 2016, ECCV.
[44] Wei Tang,et al. A Comprehensive Study of Weight Sharing in Graph Networks for 3D Human Pose Estimation , 2020, ECCV.
[45] Ross B. Girshick,et al. Focal Loss for Dense Object Detection , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[46] Jiahui Yu,et al. AutoSlim: Towards One-Shot Architecture Search for Channel Numbers , 2019 .
[47] Hans-Peter Seidel,et al. VNect , 2017, ACM Trans. Graph..
[48] Huiming Tang,et al. Dynamic GCN: Context-enriched Topology Learning for Skeleton-based Action Recognition , 2020, ACM Multimedia.
[49] Yifan Zhang,et al. Skeleton-Based Action Recognition With Shift Graph Convolutional Network , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[50] Hailun Xia,et al. Multi-Scale Mixed Dense Graph Convolution Network for Skeleton-Based Action Recognition , 2021, IEEE Access.
[51] Yifan Zhang,et al. Skeleton-Based Action Recognition With Multi-Stream Adaptive Graph Convolutional Networks , 2019, IEEE Transactions on Image Processing.