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Journal of Computer Science and Technology ›› 2019, Vol. 34 ›› Issue (3): 522-536.doi: 10.1007/s11390-019-1924-x
Special Issue: Artificial Intelligence and Pattern Recognition; Computer Graphics and Multimedia
Previous Articles Next Articles
Shuai Li1,2, Member, IEEE, Zheng Fang1, Wen-Feng Song1, Ai-Min Hao1, Member, IEEE, Hong Qin3,*, Member, IEEE
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In Proc. the 2017 IEEE International Conference on Computer Vision, October 2017, pp.2980-2988. [11] Papandreou G, Zhu T, Kanazawa N, Toshev A, Tompson J, Bregler C, Murphy K. Towards accurate multi-person pose estimation in the wild. In Proc. the 2017 IEEE Conference on Computer Vision and Pattern Recognition, July 2017, pp.3711-3719. [12] Chen Y, Wang Z, Peng Y, Zhang Z, Yu G, Sun J. Cascaded pyramid network for multi-person pose estimation. In Proc. the 2018 IEEE Conference on Computer Vision and Pattern Recognition, June 2018, pp.7103-7112. [13] Papandreou G, Zhu T, Chen L C, Gidaris S, Tompson J, Murphy K. PersonLab:Person pose estimation and instance segmentation with a bottom-up, partbased, geometric embedding model. arXiv:1803.08225, 2018. https://arxiv.org/abs/1803.08225, January 2019. [14] Kocabas M, Karagoz S, Akbas E. MultiPoseNet:Fast multi-person pose estimation using pose residual network. arXiv:1807.04067, 2018. https://arxiv.org/abs/1807.04067, January 2019. 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In Proc. the 24th IEEE Conference on Computer Vision and Pattern Recognition, June 2011, pp.1385-1392. [20] Dantone M, Gall J, Leistner C, Gool L V. Human pose estimation using body parts dependent joint regressors. In Proc. the 2013 IEEE Conference on Computer Vision and Pattern Recognition, June 2013, pp.3041-3048. [21] Gkioxari G, Arbelaez P, Bourdev L, Malik J. Articulated pose estimation using discriminative armlet classifiers. In Proc. the 2013 IEEE Conference on Computer Vision and Pattern Recognition, June 2013, pp.3342-3349. [22] Pishchulin L, Andriluka M, Gehler P, Schiele B. Poselet conditioned pictorial structures. In Proc. the 2013 IEEE Conference on Computer Vision and Pattern Recognition, June 2013, pp.588-595. [23] Sapp B, Taskar B. MODEC:Multimodal decomposable models for human pose estimation. In Proc. the 2013 IEEE Conference on Computer Vision and Pattern Recognition, June 2013, pp.3674-3681. [24] Toshev A, Szegedy C. DeepPose:Human pose estimation via deep neural networks. In Proc. the 2014 IEEE Conference on Computer Vision and Pattern Recognition, June 2014, pp.1653-1660. [25] Zhang Z, Luo P, Loy C C, Tang X. Facial landmark detection by deep multi-task learning. In Proc. the 13th European Conference on Computer Vision, September 2014, pp.94-108. [26] Wang J, Zhang J, Luo C, Chen F. Joint head pose and facial landmark regression from depth images.Computational Visual Media, 2017, 3(3):229-241. [27] Tompson J J, Jain A, LeCun Y, Bregler C. Joint training of a convolutional network and a graphical model for human pose estimation. In Proc. the 2014 Annual Conference on Neural Information Processing Systems, December 2014, pp.1799-1807. [28] Chu X, Yang W, Ouyang W, Ma C, Yuille A L, Wang X. Multi-context attention for human pose estimation. In Proc. the 2017 IEEE Conference on Computer Vision and Pattern Recognition, July 2017, pp.5669-5678. [29] Rogez G, Weinzaepfel P, Schmid C. LCR-Net:Localizationclassification-regression for human pose. In Proc. the 2017 IEEE Conference on Computer Vision and Pattern Recognition, July 2017, pp.1216-1224. [30] Fang H, Xie S, Tai Y W, Lu C. RMPE:Regional multiperson pose estimation. In Proc. the 2017 IEEE International Conference on Computer Vision, October 2017, pp.2353-2362. [31] Girshick R. Fast R-CNN. In Proc. the 2015 IEEE International Conference on Computer Vision, December 2015, pp.1440-1448. [32] Ren S, He K, Girshick R, Sun J. Faster R-CNN:Towards real-time object detection with region proposal networks. In Proc. the 2015 Annual Conference on Neural Information Processing Systems, December 2015, pp.91-99. [33] Lin T Y, Dollar P, Girshick R, He K, Hariharan B, Belongie S. Feature pyramid networks for object detection. In Proc. the 2017 IEEE Conference on Computer Vision and Pattern Recognition, July 2017, pp.936-944. [34] Lin T Y, Maire M, Belongie S, Hays J, Perona P, Ramanan D, Dollár P, Zitnick C L. Microsoft COCO:Common objects in context. In Proc. the 13th European Conference on Computer Vision, September 2014, pp.740-755. [35] Andriluka M, Pishchulin L, Gehler P, Schiele B. 2D human pose estimation:New benchmark and state of the art analysis. In Proc. the 2014 IEEE Conference on Computer Vision and Pattern Recognition, June 2014, pp.3686-3693. [36] Paszke A, Gross S, Chintala S, Chanan G, Yang E, DeVito Z, Lin Z, Desmaison A, Antiga L, Lerer A. Automatic differentiation in pytorch. In Proc. the 2017 Annual Conference on Neural Information Processing Systems Autodiff Workshop, December 2017. |
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