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In-context generation is a key component of large language models' (LLMs) open-task generalization capability.
Learning photographic global tonal adjustment with a database of input / output image pairs
Vladimir Bychkovsky, Sylvain Paris, Eric Chan, and Frédo Durand · 2011
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Indoor segmentation and support inference from rgbd images
Nathan Silberman, Derek Hoiem, Pushmeet Kohli, and Rob Fergus · 2012
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Auto-encoding variational bayes
Diederik P Kingma · 2013
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Removing rain from single images via a deep detail network
Xueyang Fu, Jiabin Huang, Delu Zeng, Yue Huang, Xinghao Ding, and John Paisley · 2017
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Deep multi-scale convolutional neural network for dynamic scene deblurring
Seungjun Nah, Tae Hyun Kim, and Kyoung Mu Lee · 2017
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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
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Deep joint rain detection and removal from a single image
Wenhan Yang, Robby T Tan, Jiashi Feng, Jiaying Liu, Zongming Guo, and Shuicheng Yan · 2017
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Scene parsing through ade20k dataset
Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2017
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Deep retinex decomposition for low-light enhancement
Chen Wei, Wenjing Wang, Wenhan Yang, and Jiaying Liu · 2018
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Language models are few-shot learners
Tom B Brown · 2020
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, T. J. Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff Wu, Clemens Winter, Christopher 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
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
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Language models are few-shot learners
Ben Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, A Neelakantan, P Shyam, G Sastry, A Askell, S Agarwal, et al · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Estimating and exploiting the aleatoric uncertainty in surface normal estimation
Gwangbin Bae, Ignas Budvytis, and Roberto Cipolla · 2021
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Bjorn Ommer · 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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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Visual prompting via image inpainting
Amir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson, and Alexei Efros · 2022
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Masked-attention mask transformer for universal image segmentation
Bowen Cheng, Ishan Misra, Alexander G Schwing, Alexander Kirillov, and Rohit Girdhar · 2022
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Training compute-optimal large language models
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katie Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Jack W. Rae, Oriol Vinyals, and L. Sifre · 2022
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All-in-one image restoration for unknown corruption
Boyun Li, Xiao Liu, Peng Hu, Zhongqin Wu, Jiancheng Lv, and Xi Peng · 2022
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Unified-io: A unified model for vision, language, and multi-modal tasks
Jiasen Lu, Christopher Clark, Rowan Zellers, Roozbeh Mottaghi, and Aniruddha Kembhavi · 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
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
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Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, et al · 2024
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Seed-x: Multimodal models with unified multi-granularity comprehension and generation
Yuying Ge, Sijie Zhao, Jinguo Zhu, Yixiao Ge, Kun Yi, Lin Song, Chen Li, Xiaohan Ding, and Ying Shan · 2024
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Instructdiffusion: A generalist modeling interface for vision tasks
Zigang Geng, Binxin Yang, Tiankai Hang, Chen Li, Shuyang Gu, Ting Zhang, Jianmin Bao, Zheng Zhang, Houqiang Li, Han Hu, et al · 2024
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Geneval: An object-focused framework for evaluating text-to-image alignment
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Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
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
Cited alongside, same era.
Inverted pyramid multi-task transformer for dense scene understanding
Hanrong Ye and Dan Xu · 2022
Cited alongside, same era.
Openflamingo: An open-source framework for training large autoregressive vision-language models
Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Yitzhak Gadre, Shiori Sagawa, Jenia Jitsev, Simon Kornblith, Pang Wei Koh, Gabriel Ilharco, Mitchell Wortsman, and Ludwig Schmidt · 2023
Cited alongside, same era.
Improving image generation with better captions
James Betker, Gabriel Goh, Li Jing, Tim Brooks, Jianfeng Wang, Linjie Li, Long Ouyang, Juntang Zhuang, Joyce Lee, Yufei Guo, et al · 2023
Cited alongside, same era.
Instructpix2pix: Learning to follow image editing instructions
Tim Brooks, Aleksander Holynski, and Alexei A Efros · 2023
Cited alongside, same era.
Dreamllm: Synergistic multimodal comprehension and creation
Runpei Dong, Chunrui Han, Yuang Peng, Zekun Qi, Zheng Ge, Jinrong Yang, Liang Zhao, Jianjian Sun, Hongyu Zhou, Haoran Wei, et al · 2023
Cited alongside, same era.
Instructcv: Instruction-tuned text-to-image diffusion models as vision generalists
Yulu Gan, Sungwoo Park, Alexander Schubert, Anthony Philippakis, and Ahmed M Alaa · 2023
Cited alongside, same era.
Dhruba Ghosh, Hannaneh Hajishirzi, and Ludwig Schmidt · 2024
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Freeedit: Mask-free reference-based image editing with multi-modal instruction
Runze He, Kai Ma, Linjiang Huang, Shaofei Huang, Jialin Gao, Xiaoming Wei, Jiao Dai, Jizhong Han, and Si Liu · 2024
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Repurposing diffusion-based image generators for monocular depth estimation
Bingxin Ke, Anton Obukhov, Shengyu Huang, Nando Metzger, Rodrigo Caye Daudt, and Konrad Schindler · 2024
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Imagefolder: Autoregressive image generation with folded tokens
Xiang Li, Hao Chen, Kai Qiu, Jason Kuen, Jiuxiang Gu, Bhiksha Raj, and Zhe Lin · 2024
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Motionclone: Training-free motion cloning for controllable video generation
Pengyang Ling, Jiazi Bu, Pan Zhang, Xiaoyi Dong, Yuhang Zang, Tong Wu, Huaian Chen, Jiaqi Wang, and Yi Jin · 2024
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Open-magvit2: An open-source project toward democratizing auto-regressive visual generation
Zhuoyan Luo, Fengyuan Shi, Yixiao Ge, Yujiu Yang, Limin Wang, and Ying Shan · 2024
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Star: Scale-wise text-to-image generation via auto-regressive representations
Xiaoxiao Ma, Mohan Zhou, Tao Liang, Yalong Bai, Tiejun Zhao, Huaian Chen, and Yi Jin · 2024
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Rb-modulation: Training-free personalization of diffusion models using stochastic optimal control
Litu Rout, Yujia Chen, Nataniel Ruiz, Abhishek Kumar, Constantine Caramanis, Sanjay Shakkottai, and Wen-Sheng Chu · 2024
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Emu edit: Precise image editing via recognition and generation tasks
Shelly Sheynin, Adam Polyak, Uriel Singer, Yuval Kirstain, Amit Zohar, Oron Ashual, Devi Parikh, and Yaniv Taigman · 2024
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Hart: Efficient visual generation with hybrid autoregressive transformer
Haotian Tang, Yecheng Wu, Shang Yang, Enze Xie, Junsong Chen, Junyu Chen, Zhuoyang Zhang, Han Cai, Yao Lu, and Song Han · 2024
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Chameleon: Mixed-modal early-fusion foundation models
Chameleon Team · 2024
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Visual autoregressive modeling: Scalable image generation via next-scale prediction
Keyu Tian, Yi Jiang, Zehuan Yuan, Bingyue Peng, and Liwei Wang · 2024
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Omnigen: Unified image generation
Shitao Xiao, Yueze Wang, Junjie Zhou, Huaying Yuan, Xingrun Xing, Ruiran Yan, Shuting Wang, Tiejun Huang, and Zheng Liu · 2024
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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
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Pyramiddrop: Accelerating your large vision-language models via pyramid visual redundancy reduction
Long Xing, Qidong Huang, Xiaoyi Dong, Jiajie Lu, Pan Zhang, Yuhang Zang, Yuhang Cao, Conghui He, Jiaqi Wang, Feng Wu, et al · 2024
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Ultraedit: Instruction-based fine-grained image editing at scale
Haozhe Zhao, Xiaojian Ma, Liang Chen, Shuzheng Si, Rujie Wu, Kaikai An, Peiyu Yu, Minjia Zhang, Qing Li, and Baobao Chang · 2024
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Transfusion: Predict the next token and diffuse images with one multi-modal model
Chunting Zhou, Lili Yu, Arun Babu, Kushal Tirumala, Michihiro Yasunaga, Leonid Shamis, Jacob Kahn, Xuezhe Ma, Luke Zettlemoyer, and Omer Levy · 2024
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Instructir: High-quality image restoration following human instructions
Marcos V Conde, Gregor Geigle, and Radu Timofte · 2025
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