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Recent breakthroughs in text-to-image synthesis have been driven by diffusion models trained on billions of image-text pairs.
An Empirical Bayes Approach to Statistics
Herbert E. Robbins · 1992
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A signal-processing framework for inverse rendering
Ravi Ramamoorthi and Pat Hanrahan · 2001
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Scalable second order optimization for deep learning, 2020
Rohan Anil, Vineet Gupta, Tomer Koren, Kevin Regan, and Yoram Singer · 2002
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2010
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A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
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Inceptionism: Going deeper into neural networks, 2015
Alexander Mordvintsev, Christopher Olah, and Mike Tyka · 2015
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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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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Gaussian error linear units (GELUs)
Dan Hendrycks and Kevin Gimpel · 2016
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue, William T Freeman, and Joshua B Tenenbaum · 2016
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Sticking the landing: Simple, lower-variance gradient estimators for variational inference, 2017
Geoffrey Roeder, Yuhuai Wu, and David Duvenaud · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Text2shape: Generating shapes from natural language by learning joint embeddings
Kevin Chen, Christopher B Choy, Manolis Savva, Angel X Chang, Thomas Funkhouser, and Silvio Savarese · 2018
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Tianyang Hu, Zixiang Chen, Hanxi Sun, Jincheng Bai, Mao Ye, and Guang Cheng · 2018
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Differentiable image parameterizations
Alexander Mordvintsev, Nicola Pezzotti, Ludwig Schubert, and Chris Olah · 2018
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Do deep generative models know what they don’t know?, 2018
Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Gorur, and Balaji Lakshminarayanan · 2018
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Parallel WaveNet: Fast high-fidelity speech synthesis
Aäron van den Oord, Yazhe Li, Igor Babuschkin, Karen Simonyan, Oriol Vinyals, Koray Kavukcuoglu, George van den Driessche, Edward Lockhart, Luis C. Cobo, Florian Stimberg, Norman Casagrande, Dominik Grewe, Seb Noury, Sander Dieleman, Erich Elsen, Nal Kalchbrenner, Heiga Zen, Alex Graves, Helen King, Tom Walters, Dan Belov, and Demis Hassabis · 2018
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Escaping Plato’s Cave: 3D shape from adversarial rendering
Philipp Henzler, Niloy J Mitra, , and Tobias Ritschel · 2019
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Probability distillation: A caveat and alternatives
Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, and Aaron C. Courville · 2019
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HoloGAN: Unsupervised learning of 3d representations from natural images
Thu Nguyen-Phuoc, Chuan Li, Lucas Theis, Christian Richardt, and Yong-Liang Yang · 2019
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ClariNet: Parallel wave generation in end-to-end text-to-speech
Wei Ping, Kainan Peng, and Jitong Chen · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Pointflow: 3d point cloud generation with continuous normalizing flows
Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, and Bharath Hariharan · 2019
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Neural reflectance fields for appearance acquisition
Sai Bi, Zexiang Xu, Pratul Srinivasan, Ben Mildenhall, Kalyan Sunkavalli, Miloš Hašan, Yannick Hold-Geoffroy, David Kriegman, and Ravi Ramamoorthi · 2020
Cited alongside, same era.
Learning gradient fields for shape generation
Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor, Zekun Hao, Serge Belongie, Noah Snavely, and Bharath Hariharan · 2020
Cited alongside, same era.
Wavegrad: Estimating gradients for waveform generation
Nanxin Chen, Yu Zhang, Heiga Zen, Ron J Weiss, Mohammad Norouzi, and William Chan · 2020
Cited alongside, same era.
Learning the stein discrepancy for training and evaluating energy-based models without sampling
Will Grathwohl, Kuan-Chieh Wang, Joern-Henrik Jacobsen, David Duvenaud, and Richard Zemel · 2020
NeRV: Neural reflectance and visibility fields for relighting and view synthesis
Pratul P Srinivasan, Boyang Deng, Xiuming Zhang, Matthew Tancik, Ben Mildenhall, and Jonathan T Barron · 2021
Later among the works it cites.
3D shape generation and completion through point-voxel diffusion
Linqi Zhou, Yilun Du, and Jiajun Wu · 2021
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Mip-NeRF 360: Unbounded anti-aliased neural radiance fields
Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, and Peter Hedman · 2022
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Diffusion models as plug-and-play priors
Alexandros Graikos, Nikolay Malkin, Nebojsa Jojic, and Dimitris Samaras · 2022
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
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Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
AR-DAE: towards unbiased neural entropy gradient estimation
Jae Hyun Lim, Aaron C. Courville, Christopher J. Pal, and Chin-Wei Huang · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 2020
Cited alongside, same era.
GRAF: Generative radiance fields for 3d-aware image synthesis
Katja Schwarz, Yiyi Liao, Michael Niemeyer, and Andreas Geiger · 2020
Cited alongside, same era.
Multiview neural surface reconstruction by disentangling geometry and appearance
Lior Yariv, Yoni Kasten, Dror Moran, Meirav Galun, Matan Atzmon, Basri Ronen, and Yaron Lipman · 2020
Cited alongside, same era.
Mip-NeRF: A multiscale representation for anti-aliasing neural radiance fields
Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 2021
Cited alongside, same era.
Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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AvatarCLIP: Zero-shot text-driven generation and animation of 3D avatars
Fangzhou Hong, Mingyuan Zhang, Liang Pan, Zhongang Cai, Lei Yang, and Ziwei Liu · 2022
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Zero-shot text-guided object generation with dream fields
Ajay Jain, Ben Mildenhall, Jonathan T. Barron, Pieter Abbeel, and Ben Poole · 2022
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CLIP-Mesh: Generating textured meshes from text using pretrained image-text models
Nasir Mohammad Khalid, Tianhao Xie, Eugene Belilovsky, and Popa Tiberiu · 2022
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Towards implicit text-guided 3d shape generation
Zhengzhe Liu, Yi Wang, Xiaojuan Qi, and Chi-Wing Fu · 2022
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MultiNeRF: A Code Release for Mip-NeRF 360, Ref-NeRF, and RawNeRF, 2022
Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, Peter Hedman, Ricardo Martin-Brualla, and Jonathan T. Barron · 2022
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2022
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StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generation
Roy Or-El, Xuan Luo, Mengyi Shan, Eli Shechtman, Jeong Joon Park, and Ira Kemelmacher-Shlizerman · 2022
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Gan2x: Non-lambertian inverse rendering of image gans
Xingang Pan, Ayush Tewari, Lingjie Liu, and Christian Theobalt · 2022
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Hierarchical text-conditional image generation with clip latents, 2022
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi · 2022
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CLIP-Forge: Towards zero-shot text-to-shape generation
Aditya Sanghi, Hang Chu, Joseph G Lambourne, Ye Wang, Chin-Yi Cheng, and Marco Fumero · 2022
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LAION-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Cade W Gordon, Ross Wightman, mehdi cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Patrick Schramowski, Srivatsa R Kundurthy, Katherine Crowson, Richard Vencu, Ludwig Schmidt, Robert Kaczmarczyk, and Jenia Jitsev · 2022
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Advances in neural rendering
Ayush Tewari, Justus Thies, Ben Mildenhall, Pratul Srinivasan, Edgar Tretschk, W Yifan, Christoph Lassner, Vincent Sitzmann, Ricardo Martin-Brualla, Stephen Lombardi, et al · 2022
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Ref-NeRF: Structured view-dependent appearance for neural radiance fields
Dor Verbin, Peter Hedman, Ben Mildenhall, Todd Zickler, Jonathan T. Barron, and Pratul P. Srinivasan · 2022
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CLIP-NeRF: Text-and-image driven manipulation of neural radiance fields
Can Wang, Menglei Chai, Mingming He, Dongdong Chen, and Jing Liao · 2022
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Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, and Yonghui Wu · 2022
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