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Solving image-to-3D from a single view is an ill-posed problem, and current neural reconstruction methods addressing it through diffusion models still rely on scene-specific optimization, constraining their generalization capability.
David Ha, Andrew M. Dai, and Quoc V. Le · 2016
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Model-agnostic meta-learning for fast adaptation of deep networks
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross B. Girshick, Kaiming He, Bharath Hariharan, and Serge J. Belongie · 2017
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Mvsnet: Depth inference for unstructured multi-view stereo
Yao Yao, Zixin Luo, Shiwei Li, Tian Fang, and Long Quan · 2018
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Fast context adaptation via meta-learning
Luisa M Zintgraf, Kyriacos Shiarlis, Vitaly Kurin, Katja Hofmann, and Shimon Whiteson · 2019
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Implicit geometric regularization for learning shapes
Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, and Yaron Lipman · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
B Mildenhall, PP Srinivasan, M Tancik, JT Barron, R Ramamoorthi, and R Ng · 2020
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Nikhila Ravi, Jeremy Reizenstein, David Novotny, Taylor Gordon, Wan-Yen Lo, Justin Johnson, and Georgia Gkioxari · 2020
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Blendedmvs: A large-scale dataset for generalized multi-view stereo networks
Yao Yao, Zixin Luo, Shiwei Li, Jingyang Zhang, Yufan Ren, Lei Zhou, Tian Fang, and Long Quan · 2020
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Jonathan T. Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P. Srinivasan · 2021
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Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo
Anpei Chen, Zexiang Xu, Fuqiang Zhao, Xiaoshuai Zhang, Fanbo Xiang, Jingyi Yu, and Hao Su · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction
Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang · 2021
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Neural fields as learnable kernels for 3d reconstruction
Francis Williams, Zan Gojcic, Sameh Khamis, Denis Zorin, Joan Bruna, Sanja Fidler, and Or Litany · 2021
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Volume rendering of neural implicit surfaces
Lior Yariv, Jiatao Gu, Yoni Kasten, and Yaron Lipman · 2021
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pixelnerf: Neural radiance fields from one or few images
Alex Yu, Vickie Ye, Matthew Tancik, and Angjoo Kanazawa · 2021
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Google scanned objects: A high-quality dataset of 3d scanned household items, 2022
Laura Downs, Anthony Francis, Nate Koenig, Brandon Kinman, Ryan Hickman, Krista Reymann, Thomas B. McHugh, and Vincent Vanhoucke · 2022
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NARF22: Neural articulated radiance fields for configuration-aware rendering
Stanley Lewis, Jana Pavlasek, and Odest Chadwicke Jenkins · 2022
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Fantasia3d: Disentangling geometry and appearance for high-quality text-to-3d content creation
Rui Chen, Yongwei Chen, Ningxin Jiao, and Kui Jia · 2023
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Hyperdiffusion: Generating implicit neural fields with weight-space diffusion
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