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In this work, we propose a new solution to 3D human pose estimation in videos.
C. Ionescu, D. Papava, V. Olaru, and C. Sminchisescu, “Human3. 6m: Large scale datasets and predictive methods for 3d human sensing in natural environments,” IEEE transactions on pattern analysis and machine intelligence , vol. 36, no. 7, pp. 1325–1339, 2013
2013
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I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in Advances in neural information processing systems , 2014, pp. 2672–2680
2014
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X. Zhou, X. Sun, W. Zhang, S. Liang, and Y. Wei, “Deep kinematic pose regression,” in European Conference on Computer Vision . Springer, 2016, pp. 186–201
2016
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J.-H. Kim, S.-W. Lee, D. Kwak, M.-O. Heo, J. Kim, J.-W. Ha, and B.-T. Zhang, “Multimodal residual learning for visual qa,” in Advances in neural information processing systems , 2016, pp. 361–369
2016
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X. Sun, J. Shang, S. Liang, and Y. Wei, “Compositional human pose regression,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 2602–2611
2017
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G. Pavlakos, X. Zhou, K. G. Derpanis, and K. Daniilidis, “Coarse-to-fine volumetric prediction for single-image 3d human pose,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 7025–7034
2017
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X. Zhou, Q. Huang, X. Sun, X. Xue, and Y. Wei, “Towards 3d human pose estimation in the wild: a weakly-supervised approach,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 398–407
2017
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C.-H. Chen and D. Ramanan, “3d human pose estimation= 2d pose estimation+ matching,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 7035–7043
2017
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J. Martinez, R. Hossain, J. Romero, and J. J. Little, “A simple yet effective baseline for 3d human pose estimation,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 2640–2649
2017
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D. Mehta, S. Sridhar, O. Sotnychenko, H. Rhodin, M. Shafiei, H.-P. Seidel, W. Xu, D. Casas, and C. Theobalt, “Vnect: Real-time 3d human pose estimation with a single rgb camera,” ACM Transactions on Graphics (TOG) , vol. 36, no. 4, p. 44, 2017
2017
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M. Lin, L. Lin, X. Liang, K. Wang, and H. Cheng, “Recurrent 3d pose sequence machines,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 810–819
2017
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J. Yu, C. Hong, Y. Rui, and D. Tao, “Multitask autoencoder model for recovering human poses,” IEEE Transactions on Industrial Electronics , vol. 65, no. 6, pp. 5060–5068, 2017
2017
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A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” Advances in neural information processing systems , vol. 30, pp. 5998–6008, 2017
2017
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D. Mehta, H. Rhodin, D. Casas, P. Fua, O. Sotnychenko, W. Xu, and C. Theobalt, “Monocular 3d human pose estimation in the wild using improved cnn supervision,” in 2017 International Conference on 3D Vision (3DV) . IEEE, 2017, pp. 506–516
2017
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H.-S. Fang, S. Xie, Y.-W. Tai, and C. Lu, “RMPE: Regional multi-person pose estimation,” in ICCV , 2017
2017
Cited alongside, same era.
H. Nam, J.-W. Ha, and J. Kim, “Dual attention networks for multimodal reasoning and matching,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 299–307
2017
Cited alongside, same era.
M. Rayat Imtiaz Hossain and J. J. Little, “Exploiting temporal information for 3d human pose estimation,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 68–84
2018
Cited alongside, same era.
K. Lee, I. Lee, and S. Lee, “Propagating lstm: 3d pose estimation based on joint interdependency,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 119–135
2018
Cited alongside, same era.
M. Kocabas, S. Karagoz, and E. Akbas, “Self-supervised learning of 3d human pose using multi-view geometry,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 1077–1086
2019
Later among the works it cites.
A. Kanazawa, J. Y. Zhang, P. Felsen, and J. Malik, “Learning 3d human dynamics from video,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 5614–5623
2019
Later among the works it cites.
G. Wei, C. Lan, W. Zeng, and Z. Chen, “View invariant 3d human pose estimation,” IEEE Transactions on Circuits and Systems for Video Technology , pp. 1–1, 2019
2019
Later among the works it cites.
J. Yu, J. Li, Z. Yu, and Q. Huang, “Multimodal transformer with multi-view visual representation for image captioning,” IEEE Transactions on Circuits and Systems for Video Technology , 2019
2019
Later among the works it cites.
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W. Yang, W. Ouyang, X. Wang, J. Ren, H. Li, and X. Wang, “3d human pose estimation in the wild by adversarial learning,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 5255–5264
2018
Cited alongside, same era.
R. Dabral, A. Mundhada, U. Kusupati, S. Afaque, A. Sharma, and A. Jain, “Learning 3d human pose from structure and motion,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 668–683
2018
Cited alongside, same era.
X. Sun, B. Xiao, F. Wei, S. Liang, and Y. Wei, “Integral human pose regression,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 529–545
2018
Cited alongside, same era.
G. Pavlakos, X. Zhou, and K. Daniilidis, “Ordinal depth supervision for 3d human pose estimation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 7307–7316
2018
Cited alongside, same era.
A. Kanazawa, M. J. Black, D. W. Jacobs, and J. Malik, “End-to-end recovery of human shape and pose,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 7122–7131
2018
Cited alongside, same era.
D. C. Luvizon, D. Picard, and H. Tabia, “2d/3d pose estimation and action recognition using multitask deep learning,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 5137–5146
2018
Cited alongside, same era.
K.-H. Lee, X. Chen, G. Hua, H. Hu, and X. He, “Stacked cross attention for image-text matching,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 201–216
2018
Cited alongside, same era.
D. Pavllo, C. Feichtenhofer, D. Grangier, and M. Auli, “3d human pose estimation in video with temporal convolutions and semi-supervised training,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 7753–7762
2019
Cited alongside, same era.
X. Li, J. Song, L. Gao, X. Liu, W. Huang, X. He, and C. Gan, “Beyond rnns: Positional self-attention with co-attention for video question answering,” in Proceedings of the AAAI Conference on Artificial Intelligence , vol. 33, 2019, pp. 8658–8665
2019
Later among the works it cites.
Y. Cai, L. Ge, J. Liu, J. Cai, T.-J. Cham, J. Yuan, and N. M. Thalmann, “Exploiting spatial-temporal relationships for 3d pose estimation via graph convolutional networks,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 2272–2281
2019
Later among the works it cites.
Y. Cheng, B. Yang, B. Wang, W. Yan, and R. T. Tan, “Occlusion-aware networks for 3d human pose estimation in video,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 723–732
2019
Later among the works it cites.
2019
Later among the works it cites.
Z. Cao, G. H. Martinez, T. Simon, S.-E. Wei, and Y. A. Sheikh, “Openpose: realtime multi-person 2d pose estimation using part affinity fields,” IEEE transactions on pattern analysis and machine intelligence , 2019
2019
Later among the works it cites.
B. Wandt and B. Rosenhahn, “Repnet: Weakly supervised training of an adversarial reprojection network for 3d human pose estimation,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2019, pp. 7782–7791
2019
Later among the works it cites.
J. Xu, Z. Yu, B. Ni, J. Yang, X. Yang, and W. Zhang, “Deep kinematics analysis for monocular 3d human pose estimation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2020, pp. 899–908
2020
Closest in time.
2020
Closest in time.
M. Gu, Z. Zhao, W. Jin, D. Cai, and F. Wu, “Video dialog via multi-grained convolutional self-attention context multi-modal networks,” IEEE Transactions on Circuits and Systems for Video Technology , vol. 30, no. 12, pp. 4453–4466, 2020
2020
Closest in time.
S. Li, L. Ke, K. Pratama, Y.-W. Tai, C.-K. Tang, and K.-T. Cheng, “Cascaded deep monocular 3d human pose estimation with evolutionary training data,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2020, pp. 6173–6183
2020
Closest in time.