Structured 3D Latents for Scalable and Versatile 3D Generation

Generative adversarial nets

Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014

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Deep unsupervised learning using nonequilibrium thermodynamics

Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015

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V-net: Fully convolutional neural networks for volumetric medical image segmentation

Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi · 2016

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Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network

Wenzhe Shi, Jose Caballero, Ferenc Huszár, Johannes Totz, Andrew P Aitken, Rob Bishop, Daniel Rueckert, and Zehan Wang · 2016

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Rethinking the inception architecture for computer vision

Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016

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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling

Jiajun Wu, Chengkai Zhang, Tianfan Xue, Bill Freeman, and Josh Tenenbaum · 2016

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Gans trained by a two time-scale update rule converge to a local nash equilibrium

Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017

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Decoupled weight decay regularization

Original

I Loshchilov · 2017

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Pointnet++: Deep hierarchical feature learning on point sets in a metric space

Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017

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Attention is all you need

A Vaswani · 2017

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O-cnn: octree-based convolutional neural networks for 3d shape analysis

Peng-Shuai Wang, Yang Liu, Yu-Xiao Guo, Chun-Yu Sun, and Xin Tong · 2017

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Demystifying mmd gans

Mikołaj Bińkowski, Danica J Sutherland, Michael Arbel, and Arthur Gretton · 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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Visual object networks: Image generation with disentangled 3d representations

Jun-Yan Zhu, Zhoutong Zhang, Chengkai Zhang, Jiajun Wu, Antonio Torralba, Josh Tenenbaum, and Bill Freeman · 2018

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Occupancy networks: Learning 3d reconstruction in function space

Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019

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Deepsdf: Learning continuous signed distance functions for shape representation

Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019

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Language models are unsupervised multitask learners

Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019

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Root mean square layer normalization

Biao Zhang and Rico Sennrich · 2019

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Denoising diffusion probabilistic models

Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020

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Modular primitives for high-performance differentiable rendering

Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, and Timo Aila · 2020

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Neural sparse voxel fields

Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 2020

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Polygen: An autoregressive generative model of 3d meshes

Charlie Nash, Yaroslav Ganin, SM Ali Eslami, and Peter Battaglia · 2020

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3d-future: 3d furniture shape with texture

Huan Fu, Rongfei Jia, Lin Gao, Mingming Gong, Binqiang Zhao, Steve Maybank, and Dacheng Tao · 2021

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Classifier-free diffusion guidance

Jonathan Ho and Tim Salimans · 2021

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Swin transformer: Hierarchical vision transformer using shifted windows

Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021

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Mixture of volumetric primitives for efficient neural rendering

Stephen Lombardi, Tomas Simon, Gabriel Schwartz, Michael Zollhoefer, Yaser Sheikh, and Jason Saragih · 2021

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Diffusion probabilistic models for 3d point cloud generation

Shitong Luo and Wei Hu · 2021

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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 · 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, et al · 2021

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Using shape to categorize: Low-shot learning with an explicit shape bias

Stefan Stojanov, Anh Thai, and James M Rehg · 2021

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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, et al · 2022

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Tensorf: Tensorial radiance fields

Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, and Hao Su · 2022

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Abo: Dataset and benchmarks for real-world 3d object understanding

Jasmine Collins, Shubham Goel, Kenan Deng, Achleshwar Luthra, Leon Xu, Erhan Gundogdu, Xi Zhang, Tomas F Yago Vicente, Thomas Dideriksen, Himanshu Arora, et al · 2022

Cited alongside, same era.

Gram: Generative radiance manifolds for 3d-aware image generation

Yu Deng, Jiaolong Yang, Jianfeng Xiang, and Xin Tong · 2022

Cited alongside, same era.

Get3d: A generative model of high quality 3d textured shapes learned from images

Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, and Sanja Fidler · 2022

Cited alongside, same era.

Neural wavelet-domain diffusion for 3d shape generation

Ka-Hei Hui, Ruihui Li, Jingyu Hu, and Chi-Wing Fu · 2022

Cited alongside, same era.

xformers: A modular and hackable transformer modelling library

Benjamin Lefaudeux, Francisco Massa, Diana Liskovich, Wenhan Xiong, Vittorio Caggiano, Sean Naren, Min Xu, Jieru Hu, Marta Tintore, Susan Zhang, Patrick Labatut, Daniel Haziza, Luca Wehrstedt, Jeremy Reizenstein, and Grigory Sizov · 2022

Cited alongside, same era.

3d generation on imagenet

Original

Ivan Skorokhodov, Aliaksandr Siarohin, Yinghao Xu, Jian Ren, Hsin-Ying Lee, Peter Wonka, and Sergey Tulyakov · 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, et al · 2023

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3d-aware image generation using 2d diffusion models

Jianfeng Xiang, Jiaolong Yang, Binbin Huang, and Xin Tong · 2023

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Swin3d: A pretrained transformer backbone for 3d indoor scene understanding, 2023

Yu-Qi Yang, Yu-Xiao Guo, Jian-Yu Xiong, Yang Liu, Hao Pan, Peng-Shuai Wang, Xin Tong, and Baining Guo · 2023

Later among the works it cites.

3dshape2vecset: A 3d shape representation for neural fields and generative diffusion models

Biao Zhang, Jiapeng Tang, Matthias Niessner, and Peter Wonka · 2023

Later among the works it cites.