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Text-to-image diffusion models have demonstrated remarkable capability in generating realistic images from arbitrary text prompts.
Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Generative adversarial text to image synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
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Improved precision and recall metric for assessing generative models
Tuomas Kynkäänniemi, Tero Karras, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2019
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Cpgan: Content-parsing generative adversarial networks for text-to-image synthesis
Jiadong Liang, Wenjie Pei, and Feng Lu · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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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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Laion-aesthetics
Christoph Schuhmann · 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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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
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 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 L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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Df-gan: A simple and effective baseline for text-to-image synthesis
Ming Tao, Hao Tang, Fei Wu, Xiao-Yuan Jing, Bing-Kun Bao, and Changsheng Xu · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Earlier work this paper cites.
Multidiffusion: Fusing diffusion paths for controlled image generation
Omer Bar-Tal, Lior Yariv, Yaron Lipman, and Tali Dekel · 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.
Zero-shot spatial layout conditioning for text-to-image diffusion models
Guillaume Couairon, Marlene Careil, Matthieu Cord, Stéphane Lathuiliere, and Jakob Verbeek · 2023
Cited alongside, same era.
Emu: Enhancing image generation models using photogenic needles in a haystack
Xiaoliang Dai, Ji Hou, Chih-Yao Ma, Sam Tsai, Jialiang Wang, Rui Wang, Peizhao Zhang, Simon Vandenhende, Xiaofang Wang, Abhimanyu Dubey, et al · 2023
Cited alongside, same era.
Diffusion with offset noise, Jan 2023
Nicholas Guttenberg · 2023
Cited alongside, same era.
Generating features with increased crop-related diversity for few-shot object detection
Jingyi Xu, H. Le · 2023
Later among the works it cites.
Layoutdiffusion: Controllable diffusion model for layout-to-image generation
Guangcong Zheng, Xianpan Zhou, Xuewei Li, Zhongang Qi, Ying Shan, and Xi Li · 2023
Later among the works it cites.
https://github.com/discus0434/aesthetic-predictor-v2-5/ , May 2024
Aesthetic predictor v2.5 · 2024
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Training-free layout control with cross-attention guidance
Minghao Chen, Iro Laina, and Andrea Vedaldi · 2024
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Be yourself: Bounded attention for multi-subject text-to-image generation
Omer Dahary, Or Patashnik, Kfir Aberman, and Daniel Cohen-Or · 2024
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Exploiting the Signal-Leak Bias in Diffusion Models
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T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation
Kaiyi Huang, Kaiyue Sun, Enze Xie, Zhenguo Li, and Xihui Liu · 2023
Cited alongside, same era.
Long Lian, Boyi Li, Adam Yala, and Trevor Darrell · 2023
Cited alongside, same era.
Semantic-driven initial image construction for guided image synthesis in diffusion model
Jiafeng Mao, Xueting Wang, and Kiyoharu Aizawa · 2023
Cited alongside, same era.
Sdxl: Improving latent diffusion models for high-resolution image synthesis
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2023
Cited alongside, same era.
Layoutllm-t2i: Eliciting layout guidance from llm for text-to-image generation
Leigang Qu, Shengqiong Wu, Hao Fei, Liqiang Nie, and Tat-Seng Chua · 2023
Cited alongside, same era.
A picture is worth a thousand words: Principled recaptioning improves image generation
Eyal Segalis, Dani Valevski, Danny Lumen, Yossi Matias, and Yaniv Leviathan · 2023
Cited alongside, same era.
The curse of recursion: Training on generated data makes models forget
Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, and Ross Anderson · 2023
Cited alongside, same era.
Martin Nicolas Everaert, Athanasios Fitsios, Marco Bocchio, Sami Arpa, Sabine Süsstrunk, and Radhakrishna Achanta · 2024
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Initno: Boosting text-to-image diffusion models via initial noise optimization
Xiefan Guo, Jinlin Liu, Miaomiao Cui, Jiankai Li, Hongyu Yang, and Di Huang · 2024
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Cogvlm2: Visual language models for image and video understanding
Wenyi Hong, Weihan Wang, Ming Ding, Wenmeng Yu, Qingsong Lv, Yan Wang, Yean Cheng, Shiyu Huang, Junhui Ji, Zhao Xue, et al · 2024
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Ssmg: Spatial-semantic map guided diffusion model for free-form layout-to-image generation
Chengyou Jia, Minnan Luo, Zhuohang Dang, Guang Dai, Xiaojun Chang, Mengmeng Wang, and Jingdong Wang · 2024
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Common diffusion noise schedules and sample steps are flawed
Shanchuan Lin, Bingchen Liu, Jiashi Li, and Xiao Yang · 2024
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Directed diffusion: Direct control of object placement through attention guidance
Wan-Duo Kurt Ma, Avisek Lahiri, JP Lewis, Thomas Leung, and W Bastiaan Kleijn · 2024
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Generating images of rare concepts using pre-trained diffusion models
Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, and Gal Chechik · 2024
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Assessing sample quality via the latent space of generative models
Jingyi Xu, Hieu M. Le, and Dimitris Samaras · 2024
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