Fetching the paper…
Reading the bibliography…
Diffusion models (DMs) have gained prominence due to their ability to generate high-quality varied images with recent advancements in text-to-image generation.
Natural language processing with Python: analyzing text with the natural language toolkit
Steven Bird, Ewan Klein, and Edward Loper · 2009
Earlier work this paper cites.
Microsoft COCO: common objects in context
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 2014
Earlier work this paper cites.
Deepfakes: a new threat to face recognition? assessment and detection
Pavel Korshunov and Sébastien Marcel · 2018
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Open-edit: Open-domain image manipulation with open-vocabulary instructions
Xihui Liu, Zhe Lin, Jianming Zhang, Handong Zhao, Quan Tran, Xiaogang Wang, and Hongsheng Li · 2020
Earlier work this paper cites.
Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Earlier work this paper cites.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
Earlier work this paper cites.
Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Björn Ommer · 2021
Earlier work this paper cites.
Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 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, Gretchen Krueger, and Ilya Sutskever · 2021
Earlier work this paper cites.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
Earlier work this paper cites.
Blended diffusion for text-driven editing of natural images
Omri Avrahami, Dani Lischinski, and Ohad Fried · 2022
Earlier work this paper cites.
Text2live: Text-driven layered image and video editing
Omer Bar-Tal, Dolev Ofri-Amar, Rafail Fridman, Yoni Kasten, and Tali Dekel · 2022
Earlier work this paper cites.
VQGAN-CLIP: open domain image generation and editing with natural language guidance
Katherine Crowson, Stella Biderman, Daniel Kornis, Dashiell Stander, Eric Hallahan, Louis Castricato, and Edward Raff · 2022
Earlier work this paper cites.
Repaint: Inpainting using denoising diffusion probabilistic models
Andreas Lugmayr, Martin Danelljan, Andrés Romero, Fisher Yu, Radu Timofte, and Luc Van Gool · 2022
Earlier work this paper cites.
SDEdit: Guided image synthesis and editing with stochastic differential equations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2022
Earlier work this paper cites.
Simple open-vocabulary object detection
Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, and Neil Houlsby · 2022
Earlier work this paper cites.
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
Earlier work this paper cites.
Hierarchical text-conditional image generation with CLIP latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Earlier work this paper cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
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, Raphael Gontijo-Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J. Fleet, and Mohammad Norouzi · 2022
Cited alongside, same era.
Sine: Single image editing with text-to-image diffusion models, 2022
Zhixing Zhang, Ligong Han, Arnab Ghosh, Dimitris Metaxas, and Jian Ren · 2022
Cited alongside, same era.
A-star: Test-time attention segregation and retention for text-to-image synthesis
Aishwarya Agarwal, Srikrishna Karanam, K J Joseph, Apoorv Saxena, Koustava Goswami, and Balaji Vasan Srinivasan · 2023
Cited alongside, same era.
Blended latent diffusion
Omri Avrahami, Ohad Fried, and Dani Lischinski · 2023
Cited alongside, same era.
Ld-znet: A latent diffusion approach for text-based image segmentation
Koutilya PNVR, Bharat Singh, Pallabi Ghosh, Behjat Siddiquie, and David Jacobs · 2023
Closest in time.
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
Closest in time.
Emu edit: Precise image editing via recognition and generation tasks
Shelly Sheynin, Adam Polyak, Uriel Singer, Yuval Kirstain, Amit Zohar, Oron Ashual, Devi Parikh, and Yaniv Taigman · 2023
Closest in time.
Emergent correspondence from image diffusion
Luming Tang, Menglin Jia, Qianqian Wang, Cheng Perng Phoo, and Bharath Hariharan · 2023
Closest in time.
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
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Samyadeep Basu, Mehrdad Saberi, Shweta Bhardwaj, Atoosa Malemir Chegini, Daniela Massiceti, Maziar Sanjabi, Shell Xu Hu, and Soheil Feizi · 2023
Cited alongside, same era.
Instructpix2pix: Learning to follow image editing instructions
Tim Brooks, Aleksander Holynski, and Alexei A Efros · 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.
Diffedit: Diffusion-based semantic image editing with mask guidance
Guillaume Couairon, Jakob Verbeek, Holger Schwenk, and Matthieu Cord · 2023
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 Haim Bermano, Gal Chechik, and Daniel Cohen-or · 2023
Cited alongside, same era.
Focus on your instruction: Fine-grained and multi-instruction image editing by attention modulation
Qin Guo and Tianwei Lin · 2023
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 · 2023
Cited alongside, same era.
Mdp: A generalized framework for text-guided image editing by manipulating the diffusion path, 2023
Qian Wang, Biao Zhang, Michael Birsak, and Peter Wonka · 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.
Uncovering the disentanglement capability in text-to-image diffusion models
Qiucheng Wu, Yujian Liu, Handong Zhao, Ajinkya Kale, Trung Bui, Tong Yu, Zhe Lin, Yang Zhang, and Shiyu Chang · 2023
Closest in time.
Open-vocabulary panoptic segmentation with text-to-image diffusion models
Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, and Shalini De Mello · 2023
Closest in time.
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
Closest in time.
Magicbrush: A manually annotated dataset for instruction-guided image editing
Kai Zhang, Lingbo Mo, Wenhu Chen, Huan Sun, and Yu Su · 2023
Closest in time.
Guiding instruction-based image editing via multimodal large language models
Tsu-Jui Fu, Wenze Hu, Xianzhi Du, William Yang Wang, Yinfei Yang, and Zhe Gan · 2024
Closest in time.
Instructdiffusion: A generalist modeling interface for vision tasks
Zigang Geng, Binxin Yang, Tiankai Hang, Chen Li, Shuyang Gu, Ting Zhang, Jianmin Bao, Zheng Zhang, Houqiang Li, Han Hu, et al · 2024
Closest in time.
Pnp inversion: Boosting diffusion-based editing with 3 lines of code
Xuan Ju, Ailing Zeng, Yuxuan Bian, Shaoteng Liu, and Qiang Xu · 2024
Closest in time.
Conform: Contrast is all you need for high-fidelity text-to-image diffusion models
Tuna Han Salih Meral, Enis Simsar, Federico Tombari, and Pinar Yanardag · 2024
Closest in time.
https://www.prolific.com/
Prolific · 2024
Closest in time.
Hive: Harnessing human feedback for instructional visual editing
Shu Zhang, Xinyi Yang, Yihao Feng, Can Qin, Chia-Chih Chen, Ning Yu, Zeyuan Chen, Huan Wang, Silvio Savarese, Stefano Ermon, et al · 2024
Closest in time.
Segment everything everywhere all at once
Xueyan Zou, Jianwei Yang, Hao Zhang, Feng Li, Linjie Li, Jianfeng Wang, Lijuan Wang, Jianfeng Gao, and Yong Jae Lee · 2024
Closest in time.