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Image-to-Voxel Model Translation for 3D Scene Reconstruction and Segmentation

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Computer Vision – ECCV 2020 (ECCV 2020)

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Abstract

Objects class, depth, and shape are instantly reconstructed by a human looking at a 2D image. While modern deep models solve each of these challenging tasks separately, they struggle to perform simultaneous scene 3D reconstruction and segmentation. We propose a single shot image-to-semantic voxel model translation framework. We train a generator adversarially against a discriminator that verifies the object’s poses. Furthermore, trapezium-shaped voxels, volumetric residual blocks, and 2D-to-3D skip connections facilitate our model learning explicit reasoning about 3D scene structure. We collected a SemanticVoxels dataset with 116k images, ground-truth semantic voxel models, depth maps, and 6D object poses. Experiments on ShapeNet and our SemanticVoxels datasets demonstrate that our framework achieves and surpasses state-of-the-art in the reconstruction of scenes with multiple non-rigid objects of different classes. We made our model and dataset publicly available (http://www.zefirus.org/SSZ).

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Acknowledgments

The reported study was funded by Russian Foundation for Basic Research (RFBR) according to the research project N\(\mathrm {^{o}}\) 17-29-04509.

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Authors and Affiliations

  1. State Research Institute of Aviation Systems (GosNIIAS), Moscow, Russia

    Vladimir V. Kniaz, Vladimir A. Knyaz, Artem Bordodymov & Petr Moshkantsev

  2. Moscow Institute of Physics and Technology (MIPT), Dolgoprudny, Russia

    Vladimir V. Kniaz & Vladimir A. Knyaz

  3. Bruno Kessler Foundation (FBK), Trento, Italy

    Fabio Remondino

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  1. Vladimir V. Kniaz
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  2. Vladimir A. Knyaz
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  3. Fabio Remondino
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  4. Artem Bordodymov
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  5. Petr Moshkantsev
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Correspondence to Vladimir A. Knyaz .

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  1. University of Oxford, Oxford, UK

    Andrea Vedaldi

  2. Graz University of Technology, Graz, Austria

    Horst Bischof

  3. University of Freiburg, Freiburg im Breisgau, Germany

    Thomas Brox

  4. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Jan-Michael Frahm

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Kniaz, V.V., Knyaz, V.A., Remondino, F., Bordodymov, A., Moshkantsev, P. (2020). Image-to-Voxel Model Translation for 3D Scene Reconstruction and Segmentation. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, JM. (eds) Computer Vision – ECCV 2020. ECCV 2020. Lecture Notes in Computer Science(), vol 12352. Springer, Cham. https://doi.org/10.1007/978-3-030-58571-6_7

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