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The success of recent text-to-image diffusion models is largely due to their capacity to be guided by a complex text prompt, which enables users to precisely describe the desired content.
Weighted nuclear norm minimization with application to image denoising
Shuhang Gu, Lei Zhang, Wangmeng Zuo, and Xiangchu Feng · 2014
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Microsoft coco captions: Data collection and evaluation server
Xinlei Chen, Hao Fang, Tsung-Yi Lin, Ramakrishna Vedantam, Saurabh Gupta, Piotr Dollár, and C Lawrence Zitnick · 2015
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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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MMDetection: Open mmlab detection toolbox and benchmark
Kai Chen, Jiaqi Wang, Jiangmiao Pang, Yuhang Cao, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jiarui Xu, Zheng Zhang, Dazhi Cheng, Chenchen Zhu, Tianheng Cheng, Qijie Zhao, Buyu Li, Xin Lu, Rui Zhu, Yue Wu, Jifeng Dai, Jingdong Wang, Jianping Shi, Wanli Ouyang, Chen Change Loy, and Dahua Lin · 2019
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander 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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Sdedit: Image synthesis and editing with stochastic differential equations
Chenlin Meng, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2021
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
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High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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Cr-fill: Generative image inpainting with auxiliary contextual reconstruction
Yu Zeng, Zhe Lin, Huchuan Lu, and Vishal M Patel · 2021
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Instructpix2pix: Learning to follow image editing instructions
Tim Brooks, Aleksander Holynski, and Alexei A Efros · 2022
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An image is worth one word: Personalizing text-to-image generation using textual inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2022
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Prompt-to-prompt image editing with cross attention control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2022
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Imagic: Text-based real image editing with diffusion models
Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Hui-Tang Chang, Tali Dekel, Inbar Mosseri, and Michal Irani · 2022
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Multi-concept customization of text-to-image diffusion
Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, and Jun-Yan Zhu · 2022
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Erasing concepts from diffusion models
Rohit Gandikota, Joanna Materzyńska, Jaden Fiotto-Kaufman, and David Bau · 2023
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Improving negative-prompt inversion via proximal guidance
Ligong Han, Song Wen, Qi Chen, Zhixing Zhang, Kunpeng Song, Mengwei Ren, Ruijiang Gao, Yuxiao Chen, Di Liu, Qilong Zhangli, et al · 2023
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Ablating concepts in text-to-image diffusion models
Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, and Jun-Yan Zhu · 2023
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Negative-prompt inversion: Fast image inversion for editing with text-guided diffusion models
Daiki Miyake, Akihiro Iohara, Yu Saito, and Toshiyuki Tanaka · 2023
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Liunian Harold Li, Pengchuan Zhang, Haotian Zhang, Jianwei Yang, Chunyuan Li, Yiwu Zhong, Lijuan Wang, Lu Yuan, Lei Zhang, Jenq-Neng Hwang, et al · 2022
Cited alongside, same era.
Null-text inversion for editing real images using guided diffusion models
Ron Mokady, Amir Hertz, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 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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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 · 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 Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi · 2022
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Unitune: Text-driven image editing by fine tuning an image generation model on a single image
Dani Valevski, Matan Kalman, Yossi Matias, and Yaniv Leviathan · 2022
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Sega: Instructing diffusion using semantic dimensions
Manuel Brack, Felix Friedrich, Dominik Hintersdorf, Lukas Struppek, Patrick Schramowski, and Kristian Kersting · 2023
Cited alongside, same era.
Attend-and-excite: Attention-based semantic guidance for text-to-image diffusion models
Hila Chefer, Yuval Alaluf, Yael Vinker, Lior Wolf, and Daniel Cohen-Or · 2023
Cited alongside, same era.
Gaurav Parmar, Krishna Kumar Singh, Richard Zhang, Yijun Li, Jingwan Lu, and Jun-Yan Zhu · 2023
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Localizing object-level shape variations with text-to-image diffusion models
Or Patashnik, Daniel Garibi, Idan Azuri, Hadar Averbuch-Elor, and Daniel Cohen-Or · 2023
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Plug-and-play diffusion features for text-driven image-to-image translation
Narek Tumanyan, Michal Geyer, Shai Bagon, and Tali Dekel · 2023
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Dynamic prompt learning: Addressing cross-attention leakage for text-based image editing
Kai Wang, Fei Yang, Shiqi Yang, Muhammad Atif Butt, and Joost van de Weijer · 2023
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Inst-inpaint: Instructing to remove objects with diffusion models, 2023
Ahmet Burak Yildirim, Vedat Baday, Erkut Erdem, Aykut Erdem, and Aysegul Dundar · 2023
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Forget-me-not: Learning to forget in text-to-image diffusion models
Eric Zhang, Kai Wang, Xingqian Xu, Zhangyang Wang, and Humphrey Shi · 2023
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Adding conditional control to text-to-image diffusion models, 2023
Lvmin Zhang and Maneesh Agrawala · 2023
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