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We present Viewset Diffusion, a diffusion-based generator that outputs 3D objects while only using multi-view 2D data for supervision.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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3d-r2n2: A unified approach for single and multi-view 3d object reconstruction
Christopher B Choy, Danfei Xu, JunYoung Gwak, Kevin Chen, and Silvio Savarese · 2016
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Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision
Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, and Honglak Lee · 2016
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Shape completion using 3d-encoder-predictor cnns and shape synthesis
Angela Dai, Charles Ruizhongtai Qi, and Matthias Nießner · 2017
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Weakly supervised 3d reconstruction with adversarial constraint
JunYoung Gwak, Christopher B Choy, Manmohan Chandraker, Animesh Garg, and Silvio Savarese · 2017
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Multi-view supervision for single-view reconstruction via differentiable ray consistency
Shubham Tulsiani, Tinghui Zhou, Alexei A. Efros, and Jitendra Malik · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Feature-wise transformations
Vincent Dumoulin, Ethan Perez, Nathan Schucher Florian, Strub Harm de Vries, Aaron Courville, and Yoshua Bengio · 2018
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Learning category-specific mesh reconstruction from image collections
Angjoo Kanazawa, Shubham Tulsiani, Alexei A. Efros, and Jitendra Malik · 2018
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Learning shape priors for single-view 3D completion and reconstruction
Jiajun Wu, Chengkai Zhang, Xiuming Zhang, Zhoutong Zhang, William T. Freeman, and Joshua B. Tenenbaum · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Scene representation networks: Continuous 3d-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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NeRF: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Quinn Nichol · 2021
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Unsupervised learning of 3d object categories from videos in the wild
Philipp Henzler, Jeremy Reizenstein, Patrick Labatut, Roman Shapovalov, Tobias Ritschel, Andrea Vedaldi, and David Novotny · 2021
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Putting nerf on a diet: Semantically consistent few-shot view synthesis
Ajay Jain, Matthew Tancik, and Pieter Abbeel · 2021
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CodeNeRF: Disentangled neural radiance fields for object categories
Wonbong Jang and Lourdes Agapito · 2021
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Diffusion probabilistic models for 3d point cloud generation
Shitong Luo and Wei Hu · 2021
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Improved denoising diffusion probabilistic models
Alex Nichol and Prafulla Dhariwal · 2021
Cited alongside, same era.
Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction
Jeremy Reizenstein, Roman Shapovalov, Philipp Henzler, Luca Sbordone, Patrick Labatut, and David Novotny · 2021
Cited alongside, same era.
ShaRF: Shape-conditioned radiance fields from a single view
Konstantinos Rematas, Ricardo Martin-Brualla, and Vittorio Ferrari · 2021
Cited alongside, same era.
Deep marching tetrahedra: a hybrid representation for high-resolution 3d shape synthesis
Tianchang Shen, Jun Gao, Kangxue Yin, Ming-Yu Liu, and Sanja Fidler · 2021
Cited alongside, same era.
Light field networks: Neural scene representations with single-evaluation rendering
Nerfdiff: Single-image view synthesis with nerf-guided distillation from 3d-aware diffusion
Jiatao Gu, Alex Trevithick, Kai-En Lin, Joshua M Susskind, Christian Theobalt, Lingjie Liu, and Ravi Ramamoorthi · 2023
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3DGen: Triplane latent diffusion for textured mesh generation
Anchit Gupta, Wenhan Xiong, Yixin Nie, Ian Jones, and Barlas Oguz · 2023
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Efficient diffusion training via min-snr weighting strategy
Tiankai Hang, Shuyang Gu, Chen Li, Jianmin Bao, Dong Chen, Han Hu, Xin Geng, and Baining Guo · 2023
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Shape-E: Generating conditional 3d implicit functions
Heewoo Jun and Alex Nichol · 2023
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Holodiffusion: Training a 3D diffusion model using 2D images
Animesh Karnewar, Andrea Vedaldi, David Novotny, and Niloy Mitra · 2023
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Vincent Sitzmann, Semon Rezchikov, William T. Freeman, Joshua B. Tenenbaum, and Fredo Durand · 2021
Cited alongside, same era.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
Cited alongside, same era.
Ibrnet: Learning multi-view image-based rendering
Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul Srinivasan, Howard Zhou, Jonathan T. Barron, Ricardo Martin-Brualla, Noah Snavely, and Thomas Funkhouser · 2021
Cited alongside, same era.
PixelNeRF: Neural radiance fields from one or few images
Alex Yu, Vickie Ye, Matthew Tancik, and Angjoo Kanazawa · 2021
Cited alongside, same era.
Efficient geometry-aware 3D generative adversarial networks
Eric R. Chan, Connor Z. Lin, Matthew A. Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas Guibas, Jonathan Tremblay, Sameh Khamis, Tero Karras, and Gordon Wetzstein · 2022
Cited alongside, same era.
Fast and explicit neural view synthesis
Pengsheng Guo, Miguel Angel Bautista, Alex Colburn, Liang Yang, Daniel Ulbricht, Joshua M. Susskind, and Qi Shan · 2022
Cited alongside, same era.
3ddesigner: Towards photorealistic 3d object generation and editing with text-guided diffusion models
Gang Li, Heliang Zheng, Chaoyue Wang, Chang Li, Changwen Zheng, and Dacheng Tao · 2022
Cited alongside, same era.
Kai-En Lin, Lin Yen-Chen, Wei-Sheng Lai, Tsung-Yi Lin, Yi-Chang Shih, and Ravi Ramamoorthi · 2023
Closest in time.
Zero-1-to-3: Zero-shot one image to 3d object
Ruoshi Liu, Rundi Wu, Basile Van Hoorick, Pavel Tokmakov, Sergey Zakharov, and Carl Vondrick · 2023
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Realfusion: 360° reconstruction of any object from a single image
Luke Melas-Kyriazi, Christian Rupprecht, Iro Laina, and Andrea Vedaldi · 2023
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Diffrf: Rendering-guided 3d radiance field diffusion
Norman Müller, , Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder, and Matthias Nießner · 2023
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Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall · 2023
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3d neural field generation using triplane diffusion
J. Ryan Shue, Eric Ryan Chan, Ryan Po, Zachary Ankner, Jiajun Wu, and Gordon Wetzstein · 2023
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Light field neural rendering
Mohammed Suhail, Carlos Esteves, Leonid Sigal, and Ameesh Makadia · 2023
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Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation
Haochen Wang, Xiaodan Du, Jiahao Li, Raymond A. Yeh, and Greg Shakhnarovich · 2023
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Rodin: A generative model for sculpting 3d digital avatars using diffusion
Tengfei Wang, Bo Zhang, Ting Zhang, Shuyang Gu, Jianmin Bao, Tadas Baltrusaitis, Jingjing Shen, Dong Chen, Fang Wen, Qifeng Chen, and Baining Guo · 2023
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Novel view synthesis with diffusion models
Daniel Watson, William Chan, Ricardo Martin-Brualla, Jonathan Ho, Andrea Tagliasacchi, and Mohammad Norouzi · 2023
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Dove: Learning deformable 3d objects by watching videos
Shangzhe Wu, Tomas Jakab, Christian Rupprecht, and Andrea Vedaldi · 2023
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MagicPony: Learning articulated 3d animals in the wild
Shangzhe Wu, Ruining Li, Tomas Jakab, Christian Rupprecht, and Andrea Vedaldi · 2023
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Sparsefusion: Distilling view-conditioned diffusion for 3d reconstruction
Zhizhuo Zhou and Shubham Tulsiani · 2023
Closest in time.