Differentiable Volumetric Rendering: Learning Implicit 3D Representations 
without 3D Supervision

Niemeyer, Michael; Mescheder, Lars; Oechsle, Michael; Geiger, Andreas

doi:10.1109/CVPR42600.2020.00356

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Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision

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Niemeyer, Michael
Max Planck Research Group Autonomous Vision, Max Planck Institute for Intelligent Systems, Max Planck Society;
External Organizations;

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Mescheder, Lars
Max Planck Research Group Autonomous Vision, Max Planck Institute for Intelligent Systems, Max Planck Society;
External Organizations;

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Oechsle, Michael
Max Planck Research Group Autonomous Vision, Max Planck Institute for Intelligent Systems, Max Planck Society;
External Organizations;

/persons/resource/persons118754

Geiger, Andreas
Max Planck Research Group Autonomous Vision, Max Planck Institute for Intelligent Systems, Max Planck Society;
External Organizations;

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https://doi.org/10.1109/CVPR42600.2020.00356
(Publisher version)

https://doi.org/10.48550/arXiv.1912.07372
(Preprint)

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Citation

Niemeyer, M., Mescheder, L., Oechsle, M., & Geiger, A. (2020). Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020) (pp. 3501-3512). Piscataway, NJ: IEEE. doi:10.1109/CVPR42600.2020.00356.

Cite as: https://hdl.handle.net/21.11116/0000-000F-6D27-C

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