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2020 Conference Publication DeepEMD: few-shot image classification with differentiable Earth Mover's Distance and structured classifiersZhang, Chi, Cai, Yujun, Lin, Guosheng and Shen, Chunhua (2020). DeepEMD: few-shot image classification with differentiable Earth Mover's Distance and structured classifiers. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA USA, 13-19 June 2020. Piscataway, NJ USA: IEEE Computer Society. doi: 10.1109/CVPR42600.2020.01222 |
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2020 Conference Publication Learning Progressive Joint Propagation for Human Motion PredictionCai, Yujun, Huang, Lin, Wang, Yiwei, Cham, Tat-Jen, Cai, Jianfei, Yuan, Junsong, Liu, Jun, Yang, Xu, Zhu, Yiheng, Shen, Xiaohui, Liu, Ding, Liu, Jing and Thalmann, Nadia Magnenat (2020). Learning Progressive Joint Propagation for Human Motion Prediction. Computer Vision – ECCV 2020 16th European Conference, Glasgow, United Kingdom, 23-28 August 2020. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-030-58571-6_14 |
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2019 Conference Publication Exploiting spatial-temporal relationships for 3D pose estimation via graph convolutional networksCai, Yujun, Ge, Liuhao, Liu, Jun, Cai, Jianfei, Cham, Tat-Jen, Yuan, Junsong and Thalmann, Nadia Magnenat (2019). Exploiting spatial-temporal relationships for 3D pose estimation via graph convolutional networks. IEEE/CVF International Conference on Computer Vision (ICCV), Seoul South Korea, Oct 27-Nov 02, 2019. LOS ALAMITOS: Institute of Electrical and Electronics Engineers Inc.. doi: 10.1109/ICCV.2019.00236 |
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2018 Conference Publication Hand PointNet: 3D Hand Pose Estimation Using Point SetsGe, Liuhao, Cai, Yujun, Weng, Junwu and Yuan, Junsong (2018). Hand PointNet: 3D Hand Pose Estimation Using Point Sets. IEEE Computer Society. doi: 10.1109/CVPR.2018.00878 |
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2018 Conference Publication Weakly-supervised 3D hand pose estimation from monocular RGB imagesCai, Yujun, Ge, Liuhao, Cai, Jianfei and Yuan, Junsong (2018). Weakly-supervised 3D hand pose estimation from monocular RGB images. Springer Verlag. doi: 10.1007/978-3-030-01231-1_41 |
