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Autoregressive models have achieved significant success in image generation.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Earlier work this paper cites.
Conditional image generation with pixelcnn decoders
Aaron Van den Oord, Nal Kalchbrenner, Lasse Espeholt, Oriol Vinyals, Alex Graves, et al · 2016
Earlier work this paper cites.
Fast generation for convolutional autoregressive models
Prajit Ramachandran, Tom Le Paine, Pooya Khorrami, Mohammad Babaeizadeh, Shiyu Chang, Yang Zhang, Mark Hasegawa-Johnson, Roy Campbell, and Thomas Huang · 2017
Earlier work this paper cites.
Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
Earlier work this paper cites.
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
Earlier work this paper cites.
Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 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, et al · 2019
Earlier work this paper cites.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Autoregressive score matching
Chenlin Meng, Lantao Yu, Yang Song, Jiaming Song, and Stefano Ermon · 2020
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Very deep vaes generalize autoregressive models and can outperform them on images
Rewon Child · 2021
Earlier work this paper cites.
Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
Earlier work this paper cites.
Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Earlier work this paper cites.
Stylegan-xl: Scaling stylegan to large diverse datasets
Axel Sauer, Katja Schwarz, and Andreas Geiger · 2022
Cited alongside, same era.
Vector-quantized image modeling with improved VQGAN
Jiahui Yu, Xin Li, Jing Yu Koh, Han Zhang, Ruoming Pang, James Qin, Alexander Ku, Yuanzhong Xu, Jason Baldridge, and Yonghui Wu · 2022
Cited alongside, same era.
Cascaded diffusion models for high fidelity image generation
Jonathan Ho, Chitwan Saharia, William Chan, David J Fleet, Mohammad Norouzi, and Tim Salimans · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Shifted diffusion for text-to-image generation
Yufan Zhou, Bingchen Liu, Yizhe Zhu, Xiao Yang, Changyou Chen, and Jinhui Xu · 2023
Cited alongside, same era.
Towards accurate image coding: Improved autoregressive image generation with dynamic vector quantization
Unified-io 2: Scaling autoregressive multimodal models with vision, language, audio, and action
Jiasen Lu, Christopher Clark, Sangho Lee, Zichen Zhang, Savya Khosla, Ryan Marten, Derek Hoiem, and Aniruddha Kembhavi · 2024
Later among the works it cites.
Desigen: A pipeline for controllable design template generation
Haohan Weng, Danqing Huang, Yu Qiao, Zheng Hu, Chin-Yew Lin, Tong Zhang, and CL Chen · 2024
Later among the works it cites.
Visual autoregressive modeling: Scalable image generation via next-scale prediction
Keyu Tian, Yi Jiang, Zehuan Yuan, Bingyue Peng, and Liwei Wang · 2024
Later among the works it cites.
Boosting diffusion models with moving average sampling in frequency domain
Yurui Qian, Qi Cai, Yingwei Pan, Yehao Li, Ting Yao, Qibin Sun, and Tao Mei · 2024
Later among the works it cites.
Emu3: Next-token prediction is all you need
Xinlong Wang, Xiaosong Zhang, Zhengxiong Luo, Quan Sun, Yufeng Cui, Jinsheng Wang, Fan Zhang, Yueze Wang, Zhen Li, Qiying Yu, Yingli Zhao, Yulong Ao, Xuebin Min, Tao Li, Boya Wu, Bo Zhao, Bowen Zhang, Liangdong Wang, Guang Liu, Zheqi He, Xi Yang, Jingjing Liu, Yonghua Lin, Tiejun Huang, and Zhongyuan Wang · 2024
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Mengqi Huang, Zhendong Mao, Zhuowei Chen, and Yongdong Zhang · 2023
Cited alongside, same era.
Scaling up gans for text-to-image synthesis
Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park, Eli Shechtman, Sylvain Paris, and Taesung Park · 2023
Cited alongside, same era.
Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
Cited alongside, same era.
Self-conditioned image generation via generating representations
Tianhong Li, Dina Katabi, and Kaiming He · 2023
Cited alongside, same era.
Diffusion-driven gan inversion for multi-modal face image generation
Jihyun Kim, Changjae Oh, Hoseok Do, Soohyun Kim, and Kwanghoon Sohn · 2024
Cited alongside, same era.
Learned representation-guided diffusion models for large-image generation
Alexandros Graikos, Srikar Yellapragada, Minh-Quan Le, Saarthak Kapse, Prateek Prasanna, Joel H. Saltz, and Dimitris Samaras · 2024
Cited alongside, same era.
Show-o: One single transformer to unify multimodal understanding and generation
Jinheng Xie, Weijia Mao, Zechen Bai, David Junhao Zhang, Weihao Wang, Kevin Qinghong Lin, Yuchao Gu, Zhijie Chen, Zhenheng Yang, and Mike Zheng Shou · 2024
Cited alongside, same era.
Later among the works it cites.
Finite scalar quantization: VQ-VAE made simple
Fabian Mentzer, David Minnen, Eirikur Agustsson, and Michael Tschannen · 2024
Later among the works it cites.
Large-dit-imagenet, 2024
Alpha-VLLM · 2024
Later among the works it cites.
Positive-incentive noise
Xuelong Li · 2024
Later among the works it cites.
Data augmentation of contrastive learning is estimating positive-incentive noise
Hongyuan Zhang, Yanchen Xu, Sida Huang, and Xuelong Li · 2024
Later among the works it cites.
Ai flow at the network edge
Jiawei Shao and Xuelong Li · 2025
Closest in time.
Frequency autoregressive image generation with continuous tokens
Hu Yu, Hao Luo, Hangjie Yuan, Yu Rong, and Feng Zhao · 2025
Closest in time.
Variational positive-incentive noise: How noise benefits models
Hongyuan Zhang, Sida Huang, Yubin Guo, and Xuelong Li · 2025
Closest in time.