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Deforming Radiance Fields with Cages

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Computer Vision – ECCV 2022 (ECCV 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13693))

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Abstract

Recent advances in radiance fields enable photorealistic rendering of static or dynamic 3D scenes, but still do not support explicit deformation that is used for scene manipulation or animation. In this paper, we propose a method that enables a new type of deformation of the radiance field: free-form radiance field deformation. We use a triangular mesh that encloses the foreground object called cage as an interface, and by manipulating the cage vertices, our approach enables the free-form deformation of the radiance field. The core of our approach is cage-based deformation which is commonly used in mesh deformation. We propose a novel formulation to extend it to the radiance field, which maps the position and the view direction of the sampling points from the deformed space to the canonical space, thus enabling the rendering of the deformed scene. The deformation results of the synthetic datasets and the real-world datasets demonstrate the effectiveness of our approach. Project page: https://xth430.github.io/deforming-nerf/.

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Notes

  1. 1.

    In fact, the actual number is smaller than this approximation since we only compute for points inside the cage.

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Acknowledgements

We would like to thank Daisuke Kasuga, Ryosuke Sasaki, Tomoyuki Takahata, Haruo Fujiwara, and Atsuhiro Noguchi for comments and discussions. This work was partially supported by JST AIP Acceleration Research JPMJCR20U3, Moonshot R &D Grant Number JPMJPS2011, CREST Grant Number JPMJCR2015, JSPS KAKENHI Grant Number JP19H01115 and Basic Research Grant (Super AI) of Institute for AI and Beyond of the University of Tokyo.

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Authors and Affiliations

  1. The University of Tokyo, Tokyo, Japan

    Tianhan Xu & Tatsuya Harada

  2. RIKEN, Tokyo, Japan

    Tatsuya Harada

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  1. Tianhan Xu
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Correspondence to Tatsuya Harada .

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Editors and Affiliations

  1. Tel Aviv University, Tel Aviv, Israel

    Shai Avidan

  2. University College London, London, UK

    Gabriel Brostow

  3. Google AI, Accra, Ghana

    Moustapha Cissé

  4. University of Catania, Catania, Italy

    Giovanni Maria Farinella

  5. Facebook (United States), Menlo Park, CA, USA

    Tal Hassner

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Xu, T., Harada, T. (2022). Deforming Radiance Fields with Cages. In: Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T. (eds) Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science, vol 13693. Springer, Cham. https://doi.org/10.1007/978-3-031-19827-4_10

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