Fetching the paper…
Reading the bibliography…
When analyzing human motion videos, the output jitters from existing pose estimators are highly-unbalanced with varied estimation errors across frames.
Kalman, R.E.: A new approach to linear filtering and prediction problems (1960)
1960
Earlier work this paper cites.
Brownrigg, D.R.: The weighted median filter. Communications of the ACM 27
1984
Earlier work this paper cites.
Fischman, M.G.: Programming time as a function of number of movement parts and changes in movement direction. Journal of Motor Behavior 16
1984
Earlier work this paper cites.
Hunter, J.S.: The exponentially weighted moving average. Journal of quality technology 18
1986
Earlier work this paper cites.
Press, W.H., Teukolsky, S.A.: Savitzky-golay smoothing filters. Computers in Physics 4
1990
Earlier work this paper cites.
Van Loan, C.: Computational frameworks for the fast Fourier transform. SIAM (1992)
1992
Earlier work this paper cites.
Young, I.T., Van Vliet, L.J.: Recursive implementation of the gaussian filter. Signal processing 44
1995
Earlier work this paper cites.
Lee, C.H., Lin, C.R., Chen, M.S.: Sliding-window filtering: an efficient algorithm for incremental mining. In: Proceedings of the tenth international conference on Information and knowledge management. pp. 263–270 (2001)
2001
Earlier work this paper cites.
Hyndman, R.J.: Moving averages. (2011)
2011
Earlier work this paper cites.
Casiez, G., Roussel, N., Vogel, D.: 1€ filter: a simple speed-based low-pass filter for noisy input in interactive systems. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. pp. 2527–2530 (2012)
2012
Earlier work this paper cites.
Ionescu, C., Papava, D., Olaru, V., Sminchisescu, C.: Human3. 6m: Large scale datasets and predictive methods for 3d human sensing in natural environments. IEEE transactions on pattern analysis and machine intelligence 36
2013
Earlier work this paper cites.
Andriluka, M., Pishchulin, L., Gehler, P., Schiele, B.: 2d human pose estimation: New benchmark and state of the art analysis. In: Proceedings of the IEEE Conference on computer Vision and Pattern Recognition. pp. 3686–3693 (2014)
2014
Earlier work this paper cites.
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: European conference on computer vision. pp. 740–755. Springer (2014)
2014
Earlier work this paper cites.
Newell, A., Yang, K., Deng, J.: Stacked hourglass networks for human pose estimation. In: European conference on computer vision. pp. 483–499. Springer (2016)
2016
Earlier work this paper cites.
Coskun, H., Achilles, F., DiPietro, R.S., Navab, N., Tombari, F.: Long short-term memory kalman filters: Recurrent neural estimators for pose regularization. 2017 IEEE International Conference on Computer Vision (ICCV) pp. 5525–5533 (2017)
2017
Earlier work this paper cites.
Martinez, J., Hossain, R., Romero, J., Little, J.J.: A simple yet effective baseline for 3d human pose estimation. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 2640–2649 (2017)
2017
Earlier work this paper cites.
Mehta, D., Rhodin, H., Casas, D., Fua, P., Sotnychenko, O., Xu, W., Theobalt, C.: Monocular 3d human pose estimation in the wild using improved cnn supervision. In: 2017 international conference on 3D vision (3DV). pp. 506–516. IEEE (2017)
2017
Earlier work this paper cites.
Mehta, D., Sridhar, S., Sotnychenko, O., Rhodin, H., Shafiei, M., Seidel, H.P., Xu, W., Casas, D., Theobalt, C.: Vnect: Real-time 3d human pose estimation with a single rgb camera. ACM Transactions on Graphics (TOG) 36
2017
Earlier work this paper cites.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. Advances in neural information processing systems 30
2017
Cited alongside, same era.
2018
Cited alongside, same era.
Chen, Y., Wang, Z., Peng, Y., Zhang, Z., Yu, G., Sun, J.: Cascaded pyramid network for multi-person pose estimation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 7103–7112 (2018)
2018
Cited alongside, same era.
Kanazawa, A., Black, M.J., Jacobs, D.W., Malik, J.: End-to-end recovery of human shape and pose. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 7122–7131 (2018)
2018
Cited alongside, same era.
Mehta, D., Sotnychenko, O., Mueller, F., Xu, W., Elgharib, M., Fua, P., Seidel, H.P., Rhodin, H., Pons-Moll, G., Theobalt, C.: Xnect: Real-time multi-person 3d motion capture with a single rgb camera. ACM Transactions on Graphics (TOG) 39
2020
Later among the works it cites.
Tripathi, S., Ranade, S., Tyagi, A., Agrawal, A.: Posenet3d: Learning temporally consistent 3d human pose via knowledge distillation. In: 2020 International Conference on 3D Vision (3DV). pp. 311–321. IEEE (2020)
2020
Later among the works it cites.
Véges, M., Lőrincz, A.: Temporal smoothing for 3d human pose estimation and localization for occluded people. In: International Conference on Neural Information Processing. pp. 557–568. Springer (2020)
2020
Later among the works it cites.
2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
von Marcard, T., Henschel, R., Black, M.J., Rosenhahn, B., Pons-Moll, G.: Recovering accurate 3d human pose in the wild using imus and a moving camera. In: Proceedings of the European Conference on Computer Vision (ECCV). pp. 601–617 (2018)
2018
Cited alongside, same era.
Mehta, D., Sotnychenko, O., Mueller, F., Xu, W., Sridhar, S., Pons-Moll, G., Theobalt, C.: Single-shot multi-person 3d pose estimation from monocular rgb. 2018 International Conference on 3D Vision (3DV) pp. 120–130 (2018)
2018
Cited alongside, same era.
Kanazawa, A., Zhang, J.Y., Felsen, P., Malik, J.: Learning 3d human dynamics from video. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 5614–5623 (2019)
2019
Cited alongside, same era.
Kolotouros, N., Pavlakos, G., Black, M.J., Daniilidis, K.: Learning to reconstruct 3d human pose and shape via model-fitting in the loop. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 2252–2261 (2019)
2019
Cited alongside, same era.
Pavllo, D., Feichtenhofer, C., Grangier, D., Auli, M.: 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. pp. 7753–7762 (2019)
2019
Cited alongside, same era.
So, D., Le, Q., Liang, C.: The evolved transformer. In: International Conference on Machine Learning. pp. 5877–5886. PMLR (2019)
2019
Cited alongside, same era.
Sun, K., Xiao, B., Liu, D., Wang, J.: Deep high-resolution representation learning for human pose estimation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 5693–5703 (2019)
2019
Cited alongside, same era.
Tsuchida, S., Fukayama, S., Hamasaki, M., Goto, M.: Aist dance video database: Multi-genre, multi-dancer, and multi-camera database for dance information processing. In: ISMIR. pp. 501–510 (2019)
2019
Cited alongside, same era.
Zeng, A., Sun, X., Huang, F., Liu, M., Xu, Q., Lin, S.C.F.: Srnet: Improving generalization in 3d human pose estimation with a split-and-recombine approach. In: ECCV (2020)
2020
Later among the works it cites.
Choi, H., Moon, G., Chang, J.Y., Lee, K.M.: Beyond static features for temporally consistent 3d human pose and shape from a video. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 1964–1973 (2021)
2021
Closest in time.
Gauss, J.F., Brandin, C., Heberle, A., Löwe, W.: Smoothing skeleton avatar visualizations using signal processing technology. SN Computer Science 2
2021
Closest in time.
Jiang, T., Camgoz, N.C., Bowden, R.: Skeletor: Skeletal transformers for robust body-pose estimation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 3394–3402 (2021)
2021
Closest in time.
Joo, H., Neverova, N., Vedaldi, A.: Exemplar fine-tuning for 3d human model fitting towards in-the-wild 3d human pose estimation. In: 2021 International Conference on 3D Vision (3DV). pp. 42–52. IEEE (2021)
2021
Closest in time.
Kim, D.Y., Chang, J.Y.: Attention-based 3d human pose sequence refinement network. Sensors 21
2021
Closest in time.
Li, J., Bian, S., Zeng, A., Wang, C., Pang, B., Liu, W., Lu, C.: Human pose regression with residual log-likelihood estimation. In: ICCV (2021)
2021
Closest in time.
Li, R., Yang, S., Ross, D.A., Kanazawa, A.: Ai choreographer: Music conditioned 3d dance generation with aist++. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 13401–13412 (October 2021)
2021
Closest in time.
Wan, Z., Li, Z., Tian, M., Liu, J., Yi, S., Li, H.: Encoder-decoder with multi-level attention for 3d human shape and pose estimation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 13033–13042 (2021)
2021
Closest in time.
Zeng, A., Sun, X., Yang, L., Zhao, N., Liu, M., Xu, Q.: Learning skeletal graph neural networks for hard 3d pose estimation. In: Proceedings of the IEEE International Conference on Computer Vision (2021)
2021
Closest in time.
Zhang, S., Zhang, Y., Bogo, F., Pollefeys, M., Tang, S.: Learning motion priors for 4d human body capture in 3d scenes. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 11343–11353 (2021)
2021
Closest in time.
2021
Closest in time.
Zhou, H., Zhang, S., Peng, J., Zhang, S., Li, J., Xiong, H., Zhang, W.: Informer: Beyond efficient transformer for long sequence time-series forecasting. In: Proceedings of AAAI (2021)
2021
Closest in time.
Zhou, K., Bhatnagar, B.L., Lenssen, J.E., Pons-Moll, G.: Toch: Spatio-temporal object correspondence to hand for motion refinement. In: arXiv (May 2022)
2022
Closest in time.