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This work aims to generate natural and diverse group motions of multiple humans from textual descriptions.
Moeslund, T.B., Granum, E.: A survey of computer vision-based human motion capture. Computer Vision and Image Understanding 81
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Van der Aa, N., Luo, X., Giezeman, G.J., Tan, R.T., Veltkamp, R.C.: Umpm benchmark: A multi-person dataset with synchronized video and motion capture data for evaluation of articulated human motion and interaction. In: 2011 IEEE international conference on computer vision workshops (ICCV Workshops). pp. 1264–1269. IEEE (2011)
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Fragkiadaki, K., Levine, S., Felsen, P., Malik, J.: Recurrent network models for human dynamics. In: Proceedings of the IEEE International Conference on Computer Vision. pp. 4346–4354 (2015). https://doi.org/10.1109/ICCV.2015.494
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Plappert, M., Mandery, C., Asfour, T.: The kit motion-language dataset. Big Data 4
2016
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Martinez, J., Black, M.J., Romero, J.: On human motion prediction using recurrent neural networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 2891–2900 (2017)
2017
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Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L.u., Polosukhin, I.: Attention is all you need. In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. (eds.) Advances in Neural Information Processing Systems. vol. 30 (2017)
2017
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Barsoum, E., Kender, J., Liu, Z.: Hp-gan: Probabilistic 3d human motion prediction via gan. In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops. pp. 1418–1427 (2018)
2018
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Harvey, F.G., Pal, C.: Recurrent transition networks for character locomotion. In: ACM SIGGRAPH Asia 2018 Technical Briefs. Association for Computing Machinery, New York, NY, USA (2018). https://doi.org/10.1145/3283254.3283277, https://doi.org/10.1145/3283254.3283277
2018
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Kanazawa, A., Black, M.J., Jacobs, D.W., Malik, J.: End-to-end recovery of human shape and pose. In: Computer Vision and Pattern Recognition (CVPR) (2018)
2018
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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
Earlier work this paper cites.
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. In: 2018 International Conference on 3D Vision (3DV). pp. 120–130. IEEE (2018)
2018
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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
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Zanfir, A., Marinoiu, E., Zanfir, M., Popa, A.I., Sminchisescu, C.: Deep network for the integrated 3d sensing of multiple people in natural images. Advances in neural information processing systems 31
2018
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Doersch, C., Zisserman, A.: Sim2real transfer learning for 3d human pose estimation: motion to the rescue. Advances in Neural Information Processing Systems 32
2019
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Hernandez, A., Gall, J., Moreno, F.: Human motion prediction via spatio-temporal inpainting. In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV). pp. 7133–7142 (2019). https://doi.org/10.1109/ICCV.2019.00723
2019
Earlier work this paper cites.
Joo, H., Simon, T., Cikara, M., Sheikh, Y.: Towards social artificial intelligence: Nonverbal social signal prediction in a triadic interaction. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 10873–10883 (2019)
2019
Earlier work this paper cites.
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
Earlier work this paper cites.
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
Earlier work this paper cites.
Kolotouros, N., Pavlakos, G., Daniilidis, K.: Convolutional mesh regression for single-image human shape reconstruction. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 4501–4510 (2019)
2019
Earlier work this paper cites.
Liu, J., Shahroudy, A., Perez, M., Wang, G., Duan, L.Y., Kot, A.C.: Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding. IEEE transactions on pattern analysis and machine intelligence 42
2019
Earlier work this paper cites.
Mahmood, N., Ghorbani, N., Troje, N.F., Pons-Moll, G., Black, M.J.: AMASS: Archive of motion capture as surface shapes. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 5442–5451 (2019)
2019
Earlier work this paper cites.
Sun, Y., Ye, Y., Liu, W., Gao, W., Fu, Y., Mei, T.: Human mesh recovery from monocular images via a skeleton-disentangled representation. In: Proceedings of the IEEE/CVF international conference on computer vision. pp. 5349–5358 (2019)
2019
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Wu, Y., Kirillov, A., Massa, F., Lo, W.Y., Girshick, R.: Detectron2 (2019)
2019
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2019
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Harvey, F.G., Yurick, M., Nowrouzezahrai, D., Pal, C.: Robust motion in-betweening. ACM Transactions on Graphics (TOG)) 39
2020
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2020
Earlier work this paper cites.
Kocabas, M., Athanasiou, N., Black, M.J.: Vibe: Video inference for human body pose and shape estimation. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 5253–5263 (2020)
2020
Earlier work this paper cites.
Ng, E., Xiang, D., Joo, H., Grauman, K.: You2me: Inferring body pose in egocentric video via first and second person interactions. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 9890–9900 (2020)
2020
Earlier work this paper cites.
Wei, M., Miaomiao, L., Mathieu, S.: History repeats itself: Human motion prediction via motion attention. In: Proceedings of the European Conference on Computer Vision (2020)
2020
Earlier work this paper cites.
Zhang, Y., An, L., Yu, T., Li, X., Li, K., Liu, Y.: 4d association graph for realtime multi-person motion capture using multiple video cameras. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 1324–1333 (2020)
2020
Earlier work this paper cites.
Bain, M., Nagrani, A., Varol, G., Zisserman, A.: Frozen in time: A joint video and image encoder for end-to-end retrieval. In: IEEE International Conference on Computer Vision (2021)
2021
Cited alongside, same era.
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
Cited alongside, same era.
Duan, Y., Shi, T., Zou, Z., Lin, Y., Qian, Z., Zhang, B., Yuan, Y.: Single-shot motion completion with transformer (2021)
2021
Cited alongside, same era.
Fieraru, M., Zanfir, M., Szente, T., Bazavan, E., Olaru, V., Sminchisescu, C.: Remips: Physically consistent 3d reconstruction of multiple interacting people under weak supervision. Advances in Neural Information Processing Systems 34
2021
Cited alongside, same era.
Petrovich, M., Black, M.J., Varol, G.: TEMOS: Generating diverse human motions from textual descriptions. In: Proceedings of the European Conference on Computer Vision (2022)
2022
Later among the works it cites.
Sun, Y., Liu, W., Bao, Q., Fu, Y., Mei, T., Black, M.J.: Putting People in their Place: Monocular Regression of 3D People in Depth. In: CVPR (2022)
2022
Later among the works it cites.
Tevet, G., Gordon, B., Hertz, A., Bermano, A.H., Cohen-Or, D.: Motionclip: Exposing human motion generation to clip space. In: Proceedings of the 17th European Conference on Computer Vision. pp. 358–374 (2022)
2022
Later among the works it cites.
Wei, W.L., Lin, J.C., Liu, T.L., Liao, H.Y.M.: Capturing humans in motion: Temporal-attentive 3d human pose and shape estimation from monocular video. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 13211–13220 (2022)
2022
Later among the works it cites.
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Kocabas, M., Huang, C.H.P., Hilliges, O., Black, M.J.: Pare: Part attention regressor for 3d human body estimation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 11127–11137 (2021)
2021
Cited alongside, same era.
Kolotouros, N., Pavlakos, G., Jayaraman, D., Daniilidis, K.: Probabilistic modeling for human mesh recovery. In: Proceedings of the IEEE/CVF international conference on computer vision. pp. 11605–11614 (2021)
2021
Cited alongside, same era.
Li, Y., Takehara, H., Taketomi, T., Zheng, B., Nießner, M.: 4dcomplete: Non-rigid motion estimation beyond the observable surface. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 12706–12716 (2021)
2021
Cited alongside, same era.
Lin, K., Wang, L., Liu, Z.: Mesh graphormer. In: Proceedings of the IEEE/CVF international conference on computer vision. pp. 12939–12948 (2021)
2021
Cited alongside, same era.
Punnakkal, A.R., Chandrasekaran, A., Athanasiou, N., Quiros-Ramirez, A., Black, M.J.: Babel: Bodies, action and behavior with english labels. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 722–731 (2021)
2021
Cited alongside, same era.
Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., Krueger, G., Sutskever, I.: Learning transferable visual models from natural language supervision (2021)
2021
Cited alongside, same era.
2021
Cited alongside, same era.
2021
Cited alongside, same era.
Yuan, Y., Iqbal, U., Molchanov, P., Kitani, K., Kautz, J.: Glamr: Global occlusion-aware human mesh recovery with dynamic cameras. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 11038–11049 (2022)
2022
Later among the works it cites.
Chen, X., Jiang, B., Liu, W., Huang, Z., Fu, B., Chen, T., Yu, G.: Executing your commands via motion diffusion in latent space. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 18000–18010 (2023)
2023
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Dai, W., Li, J., Li, D., Tiong, A.M.H., Zhao, J., Wang, W., Li, B., Fung, P., Hoi, S.: Instructblip: Towards general-purpose vision-language models with instruction tuning (2023)
2023
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2023
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Guo, Y., Yang, C., Rao, A., Liang, Z., Wang, Y., Qiao, Y., Agrawala, M., Lin, D., Dai, B.: Animatediff: Animate your personalized text-to-image diffusion models without specific tuning (2023)
2023
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Jiang, A.Q., Sablayrolles, A., Mensch, A., Bamford, C., Chaplot, D.S., de las Casas, D., Bressand, F., Lengyel, G., Lample, G., Saulnier, L., Lavaud, L.R., Lachaux, M.A., Stock, P., Scao, T.L., Lavril, T., Wang, T., Lacroix, T., Sayed, W.E.: Mistral 7b (2023)
2023
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2023
Later among the works it cites.
Le, N., Pham, T., Do, T., Tjiputra, E., Tran, Q.D., Nguyen, A.: Music-driven group choreography. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 8673–8682 (2023)
2023
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2023
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Loper, M., Mahmood, N., Romero, J., Pons-Moll, G., Black, M.J.: SMPL: A Skinned Multi-Person Linear Model. Association for Computing Machinery, New York, NY, USA, 1 edn. (2023), https://doi.org/10.1145/3596711.3596800
2023
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Qiu, Z., Yang, Q., Wang, J., Feng, H., Han, J., Ding, E., Xu, C., Fu, D., Wang, J.: Psvt: End-to-end multi-person 3d pose and shape estimation with progressive video transformers. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 21254–21263 (2023)
2023
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2023
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Sun, Y., Bao, Q., Liu, W., Mei, T., Black, M.J.: TRACE: 5D Temporal Regression of Avatars with Dynamic Cameras in 3D Environments. In: CVPR (2023)
2023
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Tanaka, M., Fujiwara, K.: Role-aware interaction generation from textual description. In: ICCV (2023)
2023
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Tanaka, M., Fujiwara, K.: Role-aware interaction generation from textual description. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 15999–16009 (2023)
2023
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Tanke, J., Zhang, L., Zhao, A., Tang, C., Cai, Y., Wang, L., Wu, P.C., Gall, J., Keskin, C.: Social diffusion: Long-term multiple human motion anticipation. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 9601–9611 (2023)
2023
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Tevet, G., Raab, S., Gordon, B., Shafir, Y., Cohen-or, D., Bermano, A.H.: Human motion diffusion model. In: Proceedings of the 11th International Conference on Learning Representations (2023)
2023
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2023
Later among the works it cites.
2023
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Yuan, Y., Song, J., Iqbal, U., Vahdat, A., Kautz, J.: PhysDiff: Physics-guided human motion diffusion model. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV) (October 2023)
2023
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Zhai, Y., Huang, M., Luan, T., Dong, L., Nwogu, I., Lyu, S., Doermann, D., Yuan, J.: Language-guided human motion synthesis with atomic actions. In: Proceedings of the 31st ACM International Conference on Multimedia. pp. 5262–5271 (2023)
2023
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Zhang, J., Zhang, Y., Cun, X., Huang, S., Zhang, Y., Zhao, H., Lu, H., Shen, X.: T2m-gpt: Generating human motion from textual descriptions with discrete representations. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2023)
2023
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2024
Closest in time.
Yang, Z., Zhou, M., Shan, M., Wen, B., Xuan, Z., Hill, M., Bai, J., Qi, G.J., Wang, Y.: Omnimotiongpt: Animal motion generation with limited data. In: International Conference on Computer Vision and Pattern Recognition (CVPR) (2024)
2024
Closest in time.