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Given a set of calibrated images of a scene, we present an approach that produces a simple, compact, and actionable 3D world representation by means of 3D primitives.
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ShapeNet: An Information-Rich 3D Model Repository
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Joint 3D Object and Layout Inference from a Single RGB-D Image
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Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision
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Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image
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Adam: A Method for Stochastic Optimization
D. P. Kingma and J. Ba · 2015
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Pixelwise View Selection for Unstructured Multi-View Stereo
J. L. Schönberger, E. Zheng, J.-M. Frahm, and M. Pollefeys · 2016
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SurfaceNet: An End-to-end 3D Neural Network for Multiview Stereopsis
M. Ji, J. Gall, H. Zheng, Y. Liu, and L. Fang · 2017
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PolyFit: Polygonal Surface Reconstruction from Point Clouds
L. Nan and P. Wonka · 2017
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Learning Shape Abstractions by Assembling Volumetric Primitives
S. Tulsiani, H. Su, L. J. Guibas, A. A. Efros, and J. Malik · 2017
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Multi-view Supervision for Single-view Reconstruction via Differentiable Ray Consistency
S. Tulsiani, T. Zhou, A. A. Efros, and J. Malik · 2017
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Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearance
L. Yariv, Y. Kasten, D. Moran, M. Galun, M. Atzmon, R. Basri, and Y. Lipman · 2020
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Visibility-aware Multi-view Stereo Network
J. Zhang · 2020
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Cuboids Revisited: Learning Robust 3D Shape Fitting to Single RGB Images
F. Kluger, H. Ackermann, E. Brachmann, M. Y. Yang, and B. Rosenhahn · 2021
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CPFN: Cascaded Primitive Fitting Networks for High-Resolution Point Clouds
E.-T. Le, M. Sung, D. Ceylan, R. Mech, T. Boubekeur, and N. J. Mitra · 2021
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Unsupervised Layered Image Decomposition into Object Prototypes
T. Monnier, E. Vincent, J. Ponce, and M. Aubry · 2021
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UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction
M. Oechsle, S. Peng, and A. Geiger · 2021
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Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks
D. Paschalidou, A. Katharopoulos, A. Geiger, and S. Fidler · 2021
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NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction
P. Wang, L. Liu, Y. Liu, C. Theobalt, T. Komura, and W. Wang · 2021
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Volume Rendering of Neural Implicit Surfaces
L. Yariv, J. Gu, Y. Kasten, and Y. Lipman · 2021
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pixelNeRF: Neural Radiance Fields from One or Few Images
A. Yu, V. Ye, M. Tancik, and A. Kanazawa · 2021
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NeRS: Neural Reflectance Surfaces for Sparse-view 3D Reconstruction in the Wild
J. Y. Zhang, G. Yang, S. Tulsiani, and D. Ramanan · 2021
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Improving neural implicit surfaces geometry with patch warping
F. Darmon, B. Bascle, J.-C. Devaux, P. Monasse, and M. Aubry · 2022
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Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstruction
Q. Fu, Q. Xu, Y.-S. Ong, and W. Tao · 2022
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Differentiable Stereopsis: Meshes from multiple views using differentiable rendering
S. Goel, G. Gkioxari, and J. Malik · 2022
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Robust and Accurate Superquadric Recovery: a Probabilistic Approach
W. Liu, Y. Wu, S. Ruan, and G. S. Chirikjian · 2022
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Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency
T. Monnier, M. Fisher, A. A. Efros, and M. Aubry · 2022
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Extracting Triangular 3D Models, Materials, and Lighting From Images
J. Munkberg, W. Chen, J. Hasselgren, A. Evans, T. Shen, T. Muller, J. Gao, and S. Fidler · 2022
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MonteBoxFinder: Detecting and Filtering Primitives to Fit a Noisy Point Cloud
M. Ramamonjisoa, S. Stekovic, and V. Lepetit · 2022
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Primitive-based Shape Abstraction via Nonparametric Bayesian Inference
Y. Wu, W. Liu, S. Ruan, and G. S. Chirikjian · 2022
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Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans
R. Loiseau, E. Vincent, M. Aubry, and L. Landrieu · 2023
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Nerfstudio: A Modular Framework for Neural Radiance Field Development
M. Tancik, E. Weber, E. Ng, R. Li, B. Yi, J. Kerr, T. Wang, A. Kristoffersen, J. Austin, K. Salahi, A. Ahuja, D. McAllister, and A. Kanazawa · 2023
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PartNeRF: Generating Part-Aware Editable 3D Shapes without 3D Supervision
K. Tertikas, D. Paschalidou, B. Pan, J. J. Park, M. A. Uy, I. Emiris, Y. Avrithis, and L. Guibas · 2023
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