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Low-Rank Adaptation (LoRA) is extensively utilized in text-to-image models for the accurate rendition of specific elements like distinct characters or unique styles in generated images.
Estimation of non-normalized statistical models by score matching
Aapo Hyvärinen · 2005
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Image generation from scene graphs
Justin Johnson, Agrim Gupta, and Li Fei-Fei · 2018
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Building machines that learn and think like people
Josh Tenenbaum · 2018
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Compositional visual generation with energy based models
Yilun Du, Shuang Li, and Igor Mordatch · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Intrinsic dimensionality explains the effectiveness of language model fine-tuning
Armen Aghajanyan, Sonal Gupta, and Luke Zettlemoyer · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Quinn Nichol · 2021
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Clipscore: A reference-free evaluation metric for image captioning
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi · 2021
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Learning to compose visual relations
Nan Liu, Shuang Li, Yilun Du, Josh Tenenbaum, and Antonio Torralba · 2021
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Controllable and compositional generation with latent-space energy-based models
Weili Nie, Arash Vahdat, and Anima Anandkumar · 2021
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
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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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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
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Lora: Low-rank adaptation of large language models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2022
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Compositional visual generation with composable diffusion models
Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, and Joshua B. Tenenbaum · 2022
Cited alongside, same era.
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
Cited alongside, same era.
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
Cited alongside, same era.
Hierarchical text-conditional image generation with CLIP latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 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.
Imagenhub: Standardizing the evaluation of conditional image generation models
Max Ku, Tianle Li, Kai Zhang, Yujie Lu, Xingyu Fu, Wenwen Zhuang, and Wenhu Chen · 2023
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Multi-concept customization of text-to-image diffusion
Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, and Jun-Yan Zhu · 2023
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Composing ensembles of pre-trained models via iterative consensus
Shuang Li, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba, and Igor Mordatch · 2023
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Designbench: Exploring and benchmarking DALL-E 3 for imagining visual design
Kevin Lin, Zhengyuan Yang, Linjie Li, Jianfeng Wang, and Lijuan Wang · 2023
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Unsupervised compositional concepts discovery with text-to-image generative models
Nan Liu, Yilun Du, Shuang Li, Joshua B. Tenenbaum, and Antonio Torralba · 2023
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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, Seyed Kamyar Seyed Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J. Fleet, and Mohammad Norouzi · 2022
Cited alongside, same era.
Modeling image composition for complex scene generation
Zuopeng Yang, Daqing Liu, Chaoyue Wang, Jie Yang, and Dacheng Tao · 2022
Cited alongside, same era.
Shihan Dou, Enyu Zhou, Yan Liu, Songyang Gao, Jun Zhao, Wei Shen, Yuhao Zhou, Zhiheng Xi, Xiao Wang, Xiaoran Fan, Shiliang Pu, Jiang Zhu, Rui Zheng, Tao Gui, Qi Zhang, and Xuanjing Huang · 2023
Cited alongside, same era.
Reduce, reuse, recycle: Compositional generation with energy-based diffusion models and MCMC
Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, and Will Sussman Grathwohl · 2023
Cited alongside, same era.
Training-free structured diffusion guidance for compositional text-to-image synthesis
Weixi Feng, Xuehai He, Tsu-Jui Fu, Varun Jampani, Arjun R. Akula, Pradyumna Narayana, Sugato Basu, Xin Eric Wang, and William Yang Wang · 2023
Cited alongside, same era.
Mix-of-show: Decentralized low-rank adaptation for multi-concept customization of diffusion models
Yuchao Gu, Xintao Wang, Jay Zhangjie Wu, Yujun Shi, Yunpeng Chen, Zihan Fan, Wuyou Xiao, Rui Zhao, Shuning Chang, Weijia Wu, Yixiao Ge, Ying Shan, and Mike Zheng Shou · 2023
Cited alongside, same era.
Svdiff: Compact parameter space for diffusion fine-tuning
Ligong Han, Yinxiao Li, Han Zhang, Peyman Milanfar, Dimitris N. Metaxas, and Feng Yang · 2023
Cited alongside, same era.
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2023
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Merging loras
Simo Ryu · 2023
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Ziplora: Any subject in any style by effectively merging loras
Viraj Shah, Nataniel Ruiz, Forrester Cole, Erika Lu, Svetlana Lazebnik, Yuanzhen Li, and Varun Jampani · 2023
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Styledrop: Text-to-image generation in any style
Kihyuk Sohn, Nataniel Ruiz, Kimin Lee, Daniel Castro Chin, Irina Blok, Huiwen Chang, Jarred Barber, Lu Jiang, Glenn Entis, Yuanzhen Li, Yuan Hao, Irfan Essa, Michael Rubinstein, and Dilip Krishnan · 2023
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In-context learning unlocked for diffusion models
Zhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen, Pengcheng He, Weizhu Chen, Zhangyang Wang, and Mingyuan Zhou · 2023
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Seeking neural nuggets: Knowledge transfer in large language models from a parametric perspective
Ming Zhong, Chenxin An, Weizhu Chen, Jiawei Han, and Pengcheng He · 2023
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OMG: occlusion-friendly personalized multi-concept generation in diffusion models
Zhe Kong, Yong Zhang, Tianyu Yang, Tao Wang, Kaihao Zhang, Bizhu Wu, Guanying Chen, Wei Liu, and Wenhan Luo · 2024
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Concept weaver: Enabling multi-concept fusion in text-to-image models
Gihyun Kwon, Simon Jenni, Dingzeyu Li, Joon-Young Lee, Jong Chul Ye, and Fabian Caba Heilbron · 2024
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Xun Wu, Shaohan Huang, and Furu Wei · 2024
Closest in time.