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Generative models have been very popular in the recent years for their image generation capabilities.
Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun · 2006
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3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Deep feature interpolation for image content changes
Paul Upchurch, Jacob Gardner, Geoff Pleiss, Robert Pless, Noah Snavely, Kavita Bala, and Kilian Weinberger · 2017
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Deepfakes: a new threat to face recognition? assessment and detection
Pavel Korshunov and Sébastien Marcel · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Ganalyze: Toward visual definitions of cognitive image properties
Lore Goetschalckx, Alex Andonian, Aude Oliva, and Phillip Isola · 2019
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On the” steerability” of generative adversarial networks
Ali Jahanian, Lucy Chai, and Phillip Isola · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Disentangling disentanglement in variational autoencoders
Emile Mathieu, Tom Rainforth, Nana Siddharth, and Yee Whye Teh · 2019
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Yonglong Tian, Dilip Krishnan, and Phillip Isola · 2019
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Stargan v2: Diverse image synthesis for multiple domains
Yunjey Choi, Youngjung Uh, Jaejun Yoo, and Jung-Woo Ha · 2020
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Ganspace: Discovering interpretable gan controls
Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, and Sylvain Paris · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Closed-form factorization of latent semantics in gans
Yujun Shen and Bolei Zhou · 2020
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Interfacegan: Interpreting the disentangled face representation learned by gans
Yujun Shen, Ceyuan Yang, Xiaoou Tang, and Bolei Zhou · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Unsupervised discovery of interpretable directions in the gan latent space
Andrey Voynov and Artem Babenko · 2020
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Styleclip: Text-driven manipulation of stylegan imagery
Or Patashnik, Zongze Wu, Eli Shechtman, Daniel Cohen-Or, and Dani Lischinski · 2021
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SEGA: Instructing text-to-image models using semantic guidance
Manuel Brack, Felix Friedrich, Dominik Hintersdorf, Lukas Struppek, Patrick Schramowski, and Kristian Kersting · 2023
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Image-to-image translation with disentangled latent vectors for face editing
Yusuf Dalva, Hamza Pehlivan, Oyku Irmak Hatipoglu, Cansu Moran, and Aysegul Dundar · 2023
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Concept sliders: Lora adaptors for precise control in diffusion models
Rohit Gandikota, Joanna Materzyńska, Tingrui Zhou, Antonio Torralba, and David Bau · 2023
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Discovering interpretable directions in the semantic latent space of diffusion models
René Haas, Inbar Huberman-Spiegelglas, Rotem Mulayoff, and Tomer Michaeli · 2023
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Improving negative-prompt inversion via proximal guidance
Ligong Han, Song Wen, Qi Chen, Zhixing Zhang, Kunpeng Song, Mengwei Ren, Ruijiang Gao, Yuxiao Chen, Di Liu, Qilong Zhangli, et al · 2023
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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
Cited alongside, same era.
Closed-form factorization of latent semantics in gans
Yujun Shen and Bolei Zhou · 2021
Cited alongside, same era.
Latentclr: A contrastive learning approach for unsupervised discovery of interpretable directions
Oğuz Kaan Yüksel, Enis Simsar, Ezgi Gülperi Er, and Pinar Yanardag · 2021
Cited alongside, same era.
Vecgan: Image-to-image translation with interpretable latent directions
Yusuf Dalva, Said Fahri Altındiş, and Aysegul Dundar · 2022
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
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
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Diffusion models already have a semantic latent space
Mingi Kwon, Jaeseok Jeong, and Youngjung Uh · 2022
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Unsupervised compositional concepts discovery with text-to-image generative models
Nan Liu, Yilun Du, Shuang Li, Joshua B. Tenenbaum, and Antonio Torralba · 2023
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Null-text inversion for editing real images using guided diffusion models
Ron Mokady, Amir Hertz, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2023
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Understanding the latent space of diffusion models through the lens of riemannian geometry
Yong-Hyun Park, Mingi Kwon, Jaewoong Choi, Junghyo Jo, and Youngjung Uh · 2023
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Styleres: Transforming the residuals for real image editing with stylegan
Hamza Pehlivan, Yusuf Dalva, and Aysegul Dundar · 2023
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Stablerep: Synthetic images from text-to-image models make strong visual representation learners
Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, and Dilip Krishnan · 2023
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Unitune: Text-driven image editing by fine tuning a diffusion model on a single image
Dani Valevski, Matan Kalman, Eyal Molad, Eyal Segalis, Yossi Matias, and Yaniv Leviathan · 2023
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A latent space of stochastic diffusion models for zero-shot image editing and guidance
Chen Henry Wu and Fernando De la Torre · 2023
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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
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Zero-shot contrastive loss for text-guided diffusion image style transfer
Serin Yang, Hyunmin Hwang, and Jong Chul Ye · 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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