Fetching the paper…
Reading the bibliography…
Recent text-to-image generative models have enabled us to transform our words into vibrant, captivating imagery.
Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 1921–1930
Narek Tumanyan, Michal Geyer, Shai Bagon, and Tali Dekel. 2023 · 1930
Earlier work this paper cites.
Artificial evolution for computer graphics. In Proceedings of the 18th annual conference on Computer graphics and interactive techniques . 319–328
Karl Sims. 1991 · 1991
Earlier work this paper cites.
Evolving virtual creatures. In Proceedings of the 21st annual conference on Computer graphics and interactive techniques . 15–22
Karl Sims. 1994 · 1994
Earlier work this paper cites.
Fit and diverse: Set evolution for inspiring 3d shape galleries
Kai Xu, Hao Zhang, Daniel Cohen-Or, and Baoquan Chen. 2012 · 2012
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics. In International Conference on Machine Learning . PMLR, 2256–2265
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli. 2015 · 2015
Earlier work this paper cites.
From inspired modeling to creative modeling
Daniel Cohen-Or and Hao Zhang. 2016 · 2016
Earlier work this paper cites.
ExquiMo: An exquisite corpse tool for co-creative 3d shape modeling
Warunika Lakmini Ranaweera. 2016 · 2016
Earlier work this paper cites.
Ahmed Elgammal, Bingchen Liu, Mohamed Elhoseiny, and Marian Mazzone. 2017 · 2017
Earlier work this paper cites.
Can computers create art?. In Arts , Vol. 7. MDPI, 18
Aaron Hertzmann. 2018 · 2018
Earlier work this paper cites.
Design: Design inspiration from generative networks. In Proceedings of the European Conference on Computer Vision (ECCV) Workshops . 0–0
Othman Sbai, Mohamed Elhoseiny, Antoine Bordes, Yann LeCun, and Camille Couprie. 2018 · 2018
Earlier work this paper cites.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2020 · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020 · 2020
Earlier work this paper cites.
Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol. 2021 · 2021
Earlier work this paper cites.
Creative Sketch Generation. In International Conference on Learning Representations
Songwei Ge, Vedanuj Goswami, Larry Zitnick, and Devi Parikh. 2021 · 2021
Earlier work this paper cites.
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 · 2021
Earlier work this paper cites.
Improved denoising diffusion probabilistic models. In International Conference on Machine Learning . PMLR, 8162–8171
Alexander Quinn Nichol and Prafulla Dhariwal. 2021 · 2021
Earlier work this paper cites.
Learning transferable visual models from natural language supervision. In International Conference on Machine Learning . PMLR, 8748–8763
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.
Denoising Diffusion Implicit Models. In International Conference on Learning Representations
Jiaming Song, Chenlin Meng, and Stefano Ermon. 2021 · 2021
Cited alongside, same era.
Omri Avrahami, Ohad Fried, and Dani Lischinski. 2022 · 2022
Cited alongside, same era.
“This is my unicorn, Fluffy”: Personalizing frozen vision-language representations. In Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XX . Springer, 558–577
Niv Cohen, Rinon Gal, Eli A Meirom, Gal Chechik, and Yuval Atzmon. 2022 · 2022
Cited alongside, same era.
Cogview2: Faster and better text-to-image generation via hierarchical transformers
Ming Ding, Wendi Zheng, Wenyi Hong, and Jie Tang. 2022 · 2022
Cited alongside, same era.
Compositional visual generation with composable diffusion models. In European Conference on Computer Vision . Springer, 423–439
DiffEdit: Diffusion-based semantic image editing with mask guidance. In The Eleventh International Conference on Learning Representations
Guillaume Couairon, Jakob Verbeek, Holger Schwenk, and Matthieu Cord. 2023 · 2023
Closest in time.
Structure and content-guided video synthesis with diffusion models
Patrick Esser, Johnathan Chiu, Parmida Atighehchian, Jonathan Granskog, and Anastasis Germanidis. 2023 · 2023
Closest in time.
Prompt-to-Prompt Image Editing with Cross-Attention Control. In The Eleventh International Conference on Learning Representations
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-or. 2023 · 2023
Closest in time.
Imagic: Text-Based Real Image Editing with Diffusion Models. In Conference on Computer Vision and Pattern Recognition 2023
Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, and Michal Irani. 2023 · 2023
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, and Joshua B Tenenbaum. 2022 · 2022
Cited alongside, same era.
SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations. In International Conference on Learning Representations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon. 2022 · 2022
Cited alongside, same era.
Clip-mesh: Generating textured meshes from text using pretrained image-text models. In SIGGRAPH Asia 2022 conference papers . 1–8
Nasir Mohammad Khalid, Tianhao Xie, Eugene Belilovsky, and Tiberiu Popa. 2022 · 2022
Cited alongside, same era.
clip-interrogator
pharmapsychotic. 2022 · 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 · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 10684–10695
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 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 L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
Cited alongside, same era.
Kandinsky 2
Arseniy Shakhmatov, Anton Razzhigaev, Aleksandr Nikolich, Vladimir Arkhipkin, Igor Pavlov, Andrey Kuznetsov, and Denis Dimitrov. 2022 · 2022
Cited alongside, same era.
Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, and Jun-Yan Zhu. 2023 · 2023
Closest in time.
Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023 · 2023
Closest in time.
Zero-shot image-to-image translation. In ACM SIGGRAPH 2023 Conference Proceedings (Los Angeles, CA, USA) (SIGGRAPH ’23)
Gaurav Parmar, Krishna Kumar Singh, Richard Zhang, Yijun Li, Jingwan Lu, and Jun-Yan Zhu. 2023 · 2023
Closest in time.
DreamFusion: Text-to-3D using 2D Diffusion. In The Eleventh International Conference on Learning Representations
Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall. 2023 · 2023
Closest in time.
DreamBooth: Fine Tuning Text-to-image Diffusion Models for Subject-Driven Generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman. 2023 · 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 · 2023
Closest in time.
Make-A-Video: Text-to-Video Generation without Text-Video Data. In The Eleventh International Conference on Learning Representations
Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, Devi Parikh, Sonal Gupta, and Yaniv Taigman. 2023 · 2023
Closest in time.
Key-Locked Rank One Editing for Text-to-Image Personalization. In ACM SIGGRAPH 2023 Conference Proceedings (Los Angeles, CA, USA) (SIGGRAPH ’23)
Yoad Tewel, Rinon Gal, Gal Chechik, and Yuval Atzmon. 2023 · 2023
Closest in time.
Concept Decomposition for Visual Exploration and Inspiration
Yael Vinker, Andrey Voynov, Daniel Cohen-Or, and Ariel Shamir. 2023 · 2023
Closest in time.
P + P+ : Extended Textual Conditioning in Text-to-Image Generation
Andrey Voynov, Qinghao Chu, Daniel Cohen-Or, and Kfir Aberman. 2023 · 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 · 2023
Closest in time.
Dream3d: Zero-shot text-to-3d synthesis using 3d shape prior and text-to-image diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 20908–20918
Jiale Xu, Xintao Wang, Weihao Cheng, Yan-Pei Cao, Ying Shan, Xiaohu Qie, and Shenghua Gao. 2023 · 2023
Closest in time.
Shifted diffusion for text-to-image generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 10157–10166
Yufan Zhou, Bingchen Liu, Yizhe Zhu, Xiao Yang, Changyou Chen, and Jinhui Xu. 2023 · 2023
Closest in time.