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We present a Multi-Instance Generation (MIG) task, simultaneously generating multiple instances with diverse controls in one image.
Microsoft coco: Common objects in context, 2015
Tsung-Yi Lin, Michael Maire, Serge Belongie, Lubomir Bourdev, Ross Girshick, James Hays, Pietro Perona, Deva Ramanan, C. Lawrence Zitnick, and Piotr Dollár · 2015
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Generative adversarial text to image synthesis, 2016
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
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Adam: A method for stochastic optimization, 2017
Diederik P. Kingma and Jimmy Ba · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Attngan: Fine-grained text to image generation with attentional generative adversarial networks, 2017
Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, and Xiaodong He · 2017
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Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks, 2017
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris Metaxas · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium, 2018
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2018
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Self-attention with relative position representations
Peter Shaw, Jakob Uszkoreit, and Ashish Vaswani · 2018
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Cbam: Convolutional block attention module, 2018
Sanghyun Woo, Jongchan Park, Joon-Young Lee, and In So Kweon · 2018
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Stanza: A Python natural language processing toolkit for many human languages
Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton, and Christopher D. Manning · 2020
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Cogview: Mastering text-to-image generation via transformers
Ming Ding, Zhuoyi Yang, Wenyi Hong, Wendi Zheng, Chang Zhou, Da Yin, Junyang Lin, Xu Zou, Zhou Shao, Hongxia Yang, and Jie Tang · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, A. Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 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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ediff-i: Text-to-image diffusion models with ensemble of expert denoisers
Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Qinsheng Zhang, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, Bryan Catanzaro, Tero Karras, and Ming-Yu Liu · 2022
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Re-imagen: Retrieval-augmented text-to-image generator, 2022
Wenhu Chen, Hexiang Hu, Chitwan Saharia, and William W. Cohen · 2022
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Hierarchical text-conditional image generation with clip latents, 2022
Aditya Ramesh et al · 2022
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Classifier-free diffusion guidance
Jonathan Ho · 2022
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Elucidating the design space of diffusion-based generative models, 2022
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models, 2022
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2022
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Palette: Image-to-image diffusion models
Chitwan Saharia, William Chan, Huiwen Chang, Chris Lee, Jonathan Ho, Tim Salimans, David Fleet, and Mohammad Norouzi · 2022
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Pfb-diff: Progressive feature blending diffusion for text-driven image editing, 2023
Wenjing Huang, Shikui Tu, and Lei Xu · 2023
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Holodiffusion: Training a 3d diffusion model using 2d images
Animesh Karnewar, Andrea Vedaldi, David Novotny, and Niloy J Mitra · 2023
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Imagic: Text-based real image editing with diffusion models, 2023
Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, and Michal Irani · 2023
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick · 2023
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Gligen: Open-set grounded text-to-image generation
Yuheng Li, Haotian Liu, Qingyang Wu, Fangzhou Mu, Jianwei Yang, Jianfeng Gao, Chunyuan Li, and Yong Jae Lee · 2023
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Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, and Yonghui Wu · 2022
Cited alongside, same era.
Cross-modal contrastive learning for text-to-image generation, 2022
Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, and Yinfei Yang · 2022
Cited alongside, same era.
SpaText: Spatio-textual representation for controllable image generation
Omri Avrahami, Thomas Hayes, Oran Gafni, Sonal Gupta, Yaniv Taigman, Devi Parikh, Dani Lischinski, Ohad Fried, and Xi Yin · 2023
Cited alongside, same era.
Multidiffusion: Fusing diffusion paths for controlled image generation
Omer Bar-Tal, Lior Yariv, Yaron Lipman, and Tali Dekel · 2023
Cited alongside, same era.
Muse: Text-to-image generation via masked generative transformers
Huiwen Chang, Han Zhang, Jarred Barber, AJ Maschinot, José Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin P. Murphy, William T. Freeman, Michael Rubinstein, Yuanzhen Li, and Dilip Krishnan · 2023
Cited alongside, same era.
Attend-and-excite: Attention-based semantic guidance for text-to-image diffusion models, 2023
Hila Chefer, Yuval Alaluf, Yael Vinker, Lior Wolf, and Daniel Cohen-Or · 2023
Cited alongside, same era.
Diffedit: Diffusion-based semantic image editing with mask guidance
Guillaume Couairon, Jakob Verbeek, Holger Schwenk, and Matthieu Cord · 2023
Cited alongside, same era.
Guided image synthesis via initial image editing in diffusion model
Jiafeng Mao, Xueting Wang, and Kiyoharu Aizawa · 2023
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Dragondiffusion: Enabling drag-style manipulation on diffusion models
Chong Mou, Xintao Wang, Jiechong Song, Ying Shan, and Jian Zhang · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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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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Controllable 3d face generation with conditional style code diffusion
Xiaolong Shen, Jianxin Ma, Chang Zhou, and Zongxin Yang · 2023
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Weijia Wu, Yuzhong Zhao, Mike Zheng Shou, Hong Zhou, and Chunhua Shen · 2023
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Boxdiff: Text-to-image synthesis with training-free box-constrained diffusion
Jinheng Xie, Yuexiang Li, Yawen Huang, Haozhe Liu, Wentian Zhang, Yefeng Zheng, and Mike Zheng Shou · 2023
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Paint by example: Exemplar-based image editing with diffusion models
Binxin Yang, Shuyang Gu, Bo Zhang, Ting Zhang, Xuejin Chen, Xiaoyan Sun, Dong Chen, and Fang Wen · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Layoutdiffusion: Controllable diffusion model for layout-to-image generation
Guangcong Zheng, Xianpan Zhou, Xuewei Li, Zhongang Qi, Ying Shan, and Xi Li · 2023
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Pyramid diffusion models for low-light image enhancement
Dewei Zhou, Zongxin Yang, and Yi Yang · 2023
Later among the works it cites.