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Subject-driven text-to-image generation aims to generate customized images of the given subject based on the text descriptions, which has drawn increasing attention.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Image-to-image translation for cross-domain disentanglement
Abel Gonzalez-Garcia, Joost van de Weijer, and Yoshua Bengio · 2018
Earlier work this paper cites.
Diverse image-to-image translation via disentangled representations
Hsin-Ying Lee, Hung-Yu Tseng, Jia-Bin Huang, Maneesh Singh, and Ming-Hsuan Yang · 2018
Earlier work this paper cites.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2018
Earlier work this paper cites.
Attngan: Fine-grained text to image generation with attentional generative adversarial networks
Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, and Xiaodong He · 2018
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Manigan: Text-guided image manipulation
Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, and Philip HS Torr · 2020
Earlier work this paper cites.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
Earlier work this paper cites.
Curriculum disentangled recommendation with noisy multi-feedback
Hong Chen, Yudong Chen, Xin Wang, Ruobing Xie, Rui Wang, Feng Xia, and Wenwu Zhu · 2021
Earlier work this paper cites.
Lora: Low-rank adaptation of large language models
Edward J Hu, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al · 2021
Earlier work this paper cites.
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
Earlier work this paper cites.
Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
Earlier work this paper cites.
Multimodal disentangled representation for recommendation
Xin Wang, Hong Chen, and Wenwu Zhu · 2021
Earlier work this paper cites.
Blended diffusion for text-driven editing of natural images
Omri Avrahami, Dani Lischinski, and Ohad Fried · 2022
Cited alongside, same era.
Text2live: Text-driven layered image and video editing
Omer Bar-Tal, Dolev Ofri-Amar, Rafail Fridman, Yoni Kasten, and Tali Dekel · 2022
Cited alongside, same era.
Instructpix2pix: Learning to follow image editing instructions
Tim Brooks, Aleksander Holynski, and Alexei A Efros · 2022
Cited alongside, same era.
Dreamartist: Towards controllable one-shot text-to-image generation via contrastive prompt-tuning
Ziyi Dong, Pengxu Wei, and Liang Lin · 2022
Cited alongside, same era.
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
Disentangled representation learning
Xin Wang, Hong Chen, Si’ao Tang, Zihao Wu, and Wenwu Zhu · 2022
Later among the works it cites.
Dynamic graph neural networks under spatio-temporal distribution shift
Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Zhou Qin, and Wenwu Zhu · 2022
Later among the works it cites.
Spectral invariant learning for dynamic graphs under distribution shifts
Zeyang Zhang, Xin Wang, Ziwei Zhang, Zhou Qin, Weigao Wen, Hui Xue, Haoyang Li, and Wenwu Zhu · 2022
Later among the works it cites.
Break-a-scene: Extracting multiple concepts from a single image
Omri Avrahami, Kfir Aberman, Ohad Fried, Daniel Cohen-Or, and Dani Lischinski · 2023
Closest in time.
Muse: Text-to-image generation via masked generative transformers
Huiwen Chang, Han Zhang, Jarred Barber, AJ Maschinot, Jose Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Murphy, William T Freeman, Michael Rubinstein, et al · 2023
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Cited alongside, same era.
Prompt-to-prompt image editing with cross attention control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2022
Cited alongside, same era.
Imagic: Text-based real image editing with diffusion models
Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, and Michal Irani · 2022
Cited alongside, same era.
Diffusionclip: Text-guided diffusion models for robust image manipulation
Gwanghyun Kim, Taesung Kwon, and Jong Chul Ye · 2022
Cited alongside, same era.
Multi-concept customization of text-to-image diffusion
Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, and Jun-Yan 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.
Closest in time.
Subject-driven text-to-image generation via apprenticeship learning
Wenhu Chen, Hexiang Hu, Yandong Li, Nataniel Rui, Xuhui Jia, Ming-Wei Chang, and William W Cohen · 2023
Closest in time.
Svdiff: Compact parameter space for diffusion fine-tuning
Ligong Han, Yinxiao Li, Han Zhang, Peyman Milanfar, Dimitris Metaxas, and Feng Yang · 2023
Closest in time.
Taming encoder for zero fine-tuning image customization with text-to-image diffusion models
Xuhui Jia, Yang Zhao, Kelvin CK Chan, Yandong Li, Han Zhang, Boqing Gong, Tingbo Hou, Huisheng Wang, and Yu-Chuan Su · 2023
Closest in time.
Unified multi-modal latent diffusion for joint subject and text conditional image generation
Yiyang Ma, Huan Yang, Wenjing Wang, Jianlong Fu, and Jiaying Liu · 2023
Closest in time.
Instantbooth: Personalized text-to-image generation without test-time finetuning
Jing Shi, Wei Xiong, Zhe Lin, and Hyun Joon Jung · 2023
Closest in time.
Curriculum co-disentangled representation learning across multiple environments for social recommendation
Xin Wang, Zirui Pan, Yuwei Zhou, Hong Chen, Chendi Ge, and Wenwu Zhu · 2023
Closest in time.
Elite: Encoding visual concepts into textual embeddings for customized text-to-image generation
Yuxiang Wei, Yabo Zhang, Zhilong Ji, Jinfeng Bai, Lei Zhang, and Wangmeng Zuo · 2023
Closest in time.
Adding conditional control to text-to-image diffusion models
Lvmin Zhang and Maneesh Agrawala · 2023
Closest in time.