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Due to the difficulty in scaling up, generative adversarial networks (GANs) seem to be falling from grace on the task of text-conditioned image synthesis.
Adaptive mixtures of local experts
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David W. Opitz and Richard Maclin · 1999
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Ensemble-based classifiers
Lior Rokach · 2010
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Learning factored representations in a deep mixture of experts
David Eigen, Marc’Aurelio Ranzato, and Ilya Sutskever · 2013
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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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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
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Microsoft COCO: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 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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Generative adversarial text to image synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
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Improved techniques for training GANs
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 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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Conditional image generation with pixelcnn decoders
Aaron Van den Oord, Nal Kalchbrenner, Lasse Espeholt, Oriol Vinyals, Alex Graves, et al · 2016
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Generative visual manipulation on the natural image manifold
Jun-Yan Zhu, Philipp Krähenbühl, Eli Shechtman, and Alexei A Efros · 2016
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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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BeGAN: Boundary equilibrium generative adversarial networks
David Berthelot, Thomas Schumm, and Luke Metz · 2017
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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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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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Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
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Photo-realistic single image super-resolution using a generative adversarial network
Christian Ledig, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, et al · 2017
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Least squares generative adversarial networks
Xudong Mao, Qing Li, Haoran Xie, Raymond YK Lau, Zhen Wang, and Stephen Paul Smolley · 2017
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Temporal generative adversarial nets with singular value clipping
Masaki Saito, Eiichi Matsumoto, and Shunta Saito · 2017
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Outrageously large neural networks: The sparsely-gated mixture-of-experts layer
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, and Jeff Dean · 2017
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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 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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StackGAN: Text to photo-realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris N Metaxas · 2017
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Progressive growing of GANs for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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Which training methods for GANs do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
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Spectral normalization for generative adversarial networks
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida · 2018
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Spatially controllable image synthesis with internal representation collaging
Ryohei Suzuki, Masanori Koyama, Takeru Miyato, Taizan Yonetsuji, and Huachun Zhu · 2018
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MoCoGAN: Decomposing motion and content for video generation
Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz · 2018
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Generative image inpainting with contextual attention
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S Huang · 2018
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GAN dissection: Visualizing and understanding generative adversarial networks
David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, and Antonio Torralba · 2019
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 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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LXMERT: learning cross-modality encoder representations from transformers
GLaM: Efficient scaling of language models with mixture-of-experts
Nan Du, Yanping Huang, Andrew M Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, et al · 2022
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Switch Transformers: Scaling to trillion parameter models with simple and efficient sparsity
William Fedus, Barret Zoph, and Noam Shazeer · 2022
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Make-A-Scene: Scene-based text-to-image generation with human priors
Oran Gafni, Adam Polyak, Oron Ashual, Shelly Sheynin, Devi Parikh, and Yaniv Taigman · 2022
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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
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StyleNeRF: A style-based 3D-aware generator for high-resolution image synthesis
Jiatao Gu, Lingjie Liu, Peng Wang, and Christian Theobalt · 2022
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Hao Tan and Mohit Bansal · 2019
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Self-attention generative adversarial networks
Han Zhang, Ian Goodfellow, Dimitris Metaxas, and Augustus Odena · 2019
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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GANSpace: Discovering interpretable GAN controls
Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, and Sylvain Paris · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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On the ”steerability” of generative adversarial networks
Ali Jahanian, Lucy Chai, and Phillip Isola · 2020
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Analyzing and improving the image quality of StyleGAN
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 2022
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GLIDE: Towards photorealistic image generation and editing with text-guided diffusion models
Alexander Quinn 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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Hierarchical text-conditional image generation with CLIP latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 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 L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
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StyleGAN-XL: Scaling StyleGAN to large diverse datasets
Axel Sauer, Katja Schwarz, and Andreas Geiger · 2022
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Clip+mlp aesthetic score predictor
Christoph Schuhmann · 2022
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LAION-5B: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
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VoxGRAF: Fast 3D-aware image synthesis with sparse voxel grids
Katja Schwarz, Axel Sauer, Michael Niemeyer, Yiyi Liao, and Andreas Geiger · 2022
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Hammer: An efficient toolkit for training deep models
Yujun Shen, Zhiyi Zhang, Dingdong Yang, Yinghao Xu, Ceyuan Yang, and Jiapeng Zhu · 2022
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Deep generative models on 3D representations: A survey
Zifan Shi, Sida Peng, Yinghao Xu, Geiger Andreas, Yiyi Liao, and Yujun Shen · 2022
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Improving 3D-aware image synthesis with a geometry-aware discriminator
Zifan Shi, Yinghao Xu, Yujun Shen, Deli Zhao, Qifeng Chen, and Dit-Yan Yeung · 2022
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EpiGRAF: Rethinking training of 3D GANs
Ivan Skorokhodov, Sergey Tulyakov, Yiqun Wang, and Peter Wonka · 2022
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3D-aware image synthesis via learning structural and textural representations
Yinghao Xu, Sida Peng, Ceyuan Yang, Yujun Shen, and Bolei Zhou · 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, et al · 2022
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LAFITE: Towards language-free training for text-to-image generation
Yufan Zhou, Ruiyi Zhang, Changyou Chen, Chunyuan Li, Chris Tensmeyer, Tong Yu, Jiuxiang Gu, Jinhui Xu, and Tong Sun · 2022
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Region-based semantic factorization in GANs
Jiapeng Zhu, Yujun Shen, Yinghao Xu, Deli Zhao, and Qifeng Chen · 2022
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Muse: Text-to-image generation via masked generative transformers
Huiwen Chang, Han Zhang, Jarred Barber, AJ Maschinot, Jose Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Murphy, William T Freeman, Michael Rubinstein, et al · 2023
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Scaling up GANs for text-to-image synthesis
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StyleGAN-T: Unlocking the power of GANs for fast large-scale text-to-image synthesis
Axel Sauer, Tero Karras, Samuli Laine, Andreas Geiger, and Timo Aila · 2023
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Scaling vision-language models with sparse mixture of experts
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Learning 3d-aware image synthesis with unknown pose distribution
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Consistency models
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GALIP: Generative adversarial CLIPs for text-to-image synthesis
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Learning modulated transformation in GANs
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