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Conference Paper

Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations

MPS-Authors
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Rüegg,  Nadine
External Organizations;
Dept. Perceiving Systems, Max Planck Institute for Intelligent Systems, Max Planck Society;

/persons/resource/persons75293

Black,  Michael       
Dept. Perceiving Systems, Max Planck Institute for Intelligent Systems, Max Planck Society;

External Resource

https://doi.org/10.1609/aaai.v34i04.6008
(Publisher version)

https://doi.org/10.48550/arXiv.2001.01613
(Preprint)

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Citation

Rüegg, N., Lassner, C., Black, M., & Schindler, K. (2020). Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, the Thirty-Second Conference on Innovative Applications of Artificial Intelligence, the Tenth Symposium on Educational Advances in Artificial Intelligence (pp. 5561-5569). Palo Alto, CA: AAAI Press. doi:10.1609/aaai.v34i04.6008.


Cite as: https://hdl.handle.net/21.11116/0000-000C-E723-8
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