A Pytorch Reproduction of Masked Generative Image Transformer

Pixel recurrent neural networks

Aäron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016

Earlier work this paper cites.

BERT: pre-training of deep bidirectional transformers for language understanding

Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019

Earlier work this paper cites.

Pytorch: An imperative style, high-performance deep learning library

Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Z. Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019

Earlier work this paper cites.

Language models are few-shot learners

Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020

Earlier work this paper cites.

Taming transformers for high-resolution image synthesis

Patrick Esser, Robin Rombach, and Björn Ommer · 2020

Earlier work this paper cites.

Diffusion models beat gans on image synthesis

Prafulla Dhariwal and Alexander Nichol · 2021

Earlier work this paper cites.

Maskgit: Masked generative image transformer

Huiwen Chang, Han Zhang, Lu Jiang, Ce Liu, and William T. Freeman · 2022

Cited alongside, same era.

Masked autoencoders are scalable vision learners

Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross B. Girshick · 2022

Cited alongside, same era.

Improved masked image generation with token-critic

José Lezama, Huiwen Chang, Lu Jiang, and Irfan Essa · 2022

Cited alongside, same era.

Muse: Text-to-image generation via masked generative transformers

Huiwen Chang, Han Zhang, Jarred Barber, Aaron Maschinot, Jose Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Patrick Murphy, William T Freeman, Michael Rubinstein, et al · 2023

Cited alongside, same era.

Text-conditioned sampling framework for text-to-image generation with masked generative models

Jaewoong Lee, Sangwon Jang, Jaehyeong Jo, Jaehong Yoon, Yunji Kim, Jin-Hwa Kim, Jung-Woo Ha, and Sung Ju Hwang · 2023

Cited alongside, same era.

MAGE: masked generative encoder to unify representation learning and image synthesis

Tianhong Li, Huiwen Chang, Shlok Kumar Mishra, Han Zhang, Dina Katabi, and Dilip Krishnan · 2023

Closest in time.

Phenaki: Variable length video generation from open domain textual descriptions

Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans, Hernan Moraldo, Han Zhang, Mohammad Taghi Saffar, Santiago Castro, Julius Kunze, and Dumitru Erhan · 2023

Closest in time.

Temporally consistent transformers for video generation

Wilson Yan, Danijar Hafner, Stephen James, and Pieter Abbeel · 2023

Closest in time.

MAGVIT: masked generative video transformer

Lijun Yu, Yong Cheng, Kihyuk Sohn, José Lezama, Han Zhang, Huiwen Chang, Alexander G. Hauptmann, Ming-Hsuan Yang, Yuan Hao, Irfan Essa, and Lu Jiang · 2023

Closest in time.

Language model beats diffusion – tokenizer is key to visual generation

Original

Lijun Yu, José Lezama, Nitesh B. Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, Yong Cheng, Agrim Gupta, Xiuye Gu, Alexander G. Hauptmann, Boqing Gong, Ming-Hsuan Yang, Irfan Essa, David A. Ross, and Lu Jiang · 2023