Fetching the paper…
Reading the bibliography…
Intrinsic images, in the original sense, are image-like maps of scene properties like depth, normal, albedo or shading.
Recovering intrinsic scene characteristics
H Barrow and J Tenenbaum · 1978
Earlier work this paper cites.
Intrinsic images in the wild
Sean Bell, Kavita Bala, and Noah Snavely · 2014
Earlier work this paper cites.
Generative adversarial networks
Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
Earlier work this paper cites.
Semantic understanding of scenes through the ade20k dataset
Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2016
Earlier work this paper cites.
Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
Earlier work this paper cites.
Self-supervised intrinsic image decomposition
Michael Janner, Jiajun Wu, Tejas D Kulkarni, Ilker Yildirim, and Josh Tenenbaum · 2017
Earlier work this paper cites.
Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
Earlier work this paper cites.
Gan dissection: Visualizing and understanding generative adversarial networks
David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B Tenenbaum, William T Freeman, and Antonio Torralba · 2018
Earlier work this paper cites.
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
Earlier work this paper cites.
An introduction to variational autoencoders
Diederik P Kingma, Max Welling, et al · 2019
Earlier work this paper cites.
Generating diverse high-fidelity images with vq-vae-2
Ali Razavi, Aaron Van den Oord, and Oriol Vinyals · 2019
Earlier work this paper cites.
Inverserendernet: Learning single image inverse rendering
Ye Yu and William AP Smith · 2019
Earlier work this paper cites.
Understanding the role of individual units in a deep neural network
David Bau, Jun-Yan Zhu, Hendrik Strobelt, Agata Lapedriza, Bolei Zhou, and Antonio Torralba · 2020
Earlier work this paper cites.
Analyzing and improving the image quality of stylegan
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
Earlier work this paper cites.
Unsupervised learning for intrinsic image decomposition from a single image
Yunfei Liu, Yu Li, Shaodi You, and Feng Lu · 2020
Earlier work this paper cites.
Rgbd-gan: Unsupervised 3d representation learning from natural image datasets via rgbd image synthesis
Atsuhiro Noguchi and Tatsuya Harada · 2020
Earlier work this paper cites.
Do 2d gans know 3d shape? unsupervised 3d shape reconstruction from 2d image gans
Xingang Pan, Bo Dai, Ziwei Liu, Chen Change Loy, and Ping Luo · 2020
Earlier work this paper cites.
Interfacegan: Interpreting the disentangled face representation learned by gans
Yujun Shen, Ceyuan Yang, Xiaoou Tang, and Bolei Zhou · 2020
Earlier work this paper cites.
Unsupervised discovery of interpretable directions in the gan latent space
Andrey Voynov and Artem Babenko · 2020
Earlier work this paper cites.
Semantic hierarchy emerges in deep generative representations for scene synthesis
Ceyuan Yang, Yujun Shen, and Bolei Zhou · 2020
Earlier work this paper cites.
Robust learning through cross-task consistency
Amir R Zamir, Alexander Sax, Nikhil Cheerla, Rohan Suri, Zhangjie Cao, Jitendra Malik, and Leonidas J Guibas · 2020
Earlier work this paper cites.
Image gans meet differentiable rendering for inverse graphics and interpretable 3d neural rendering
Yuxuan Zhang, Wenzheng Chen, Huan Ling, Jun Gao, Yinan Zhang, Antonio Torralba, and Sanja Fidler · 2020
Earlier work this paper cites.
In-domain gan inversion for real image editing
Jiapeng Zhu, Yujun Shen, Deli Zhao, and Bolei Zhou · 2020
Earlier work this paper cites.
Styleflow: Attribute-conditioned exploration of stylegan-generated images using conditional continuous normalizing flows
Rameen Abdal, Peihao Zhu, Niloy J Mitra, and Peter Wonka · 2021
Cited alongside, same era.
Jojogan: One shot face stylization
Min Jin Chong and David Forsyth · 2021
Cited alongside, same era.
Stylegan of all trades: Image manipulation with only pretrained stylegan
Min Jin Chong, Hsin-Ying Lee, and David Forsyth · 2021
Cited alongside, same era.
Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
Cited alongside, same era.
Omnidata: A scalable pipeline for making multi-task mid-level vision datasets from 3d scans
Ainaz Eftekhar, Alexander Sax, Jitendra Malik, and Amir Zamir · 2021
Cited alongside, same era.
Enjoy your editing: Controllable gans for image editing via latent space navigation
Peiye Zhuang, Oluwasanmi Koyejo, and Alexander G Schwing · 2021
Later among the works it cites.
Hyperstyle: Stylegan inversion with hypernetworks for real image editing
Yuval Alaluf, Omer Tov, Ron Mokady, Rinon Gal, and Amit Bermano · 2022
Later among the works it cites.
Generative modeling for multi-task visual learning
Zhipeng Bao, Martial Hebert, and Yu-Xiong Wang · 2022
Later among the works it cites.
Visual prompting via image inpainting
Amir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson, and Alexei Efros · 2022
Later among the works it cites.
Maskgit: Masked generative image transformer
Huiwen Chang, Han Zhang, Lu Jiang, Ce Liu, and William T. Freeman · 2022
Later among the works it cites.
3d common corruptions and data augmentation
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Intrinsic image decomposition using paradigms
David Forsyth and Jason J Rock · 2021
Cited alongside, same era.
Edibert, a generative model for image editing
Thibaut Issenhuth, Ugo Tanielian, Jérémie Mary, and David Picard · 2021
Cited alongside, same era.
Generative models as a data source for multiview representation learning
Ali Jahanian, Xavier Puig, Yonglong Tian, and Phillip Isola · 2021
Cited alongside, same era.
Stylefusion: A generative model for disentangling spatial segments
Omer Kafri, Or Patashnik, Yuval Alaluf, and Daniel Cohen-Or · 2021
Cited alongside, same era.
Alias-free generative adversarial networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2021
Cited alongside, same era.
Semantic segmentation with generative models: Semi-supervised learning and strong out-of-domain generalization
Daiqing Li, Junlin Yang, Karsten Kreis, Antonio Torralba, and Sanja Fidler · 2021
Cited alongside, same era.
Editgan: High-precision semantic image editing
Huan Ling, Karsten Kreis, Daiqing Li, Seung Wook Kim, Antonio Torralba, and Sanja Fidler · 2021
Cited alongside, same era.
Oğuzhan Fatih Kar, Teresa Yeo, Andrei Atanov, and Amir Zamir · 2022
Later among the works it cites.
Gan2x: Non-lambertian inverse rendering of image gans
Xingang Pan, Ayush Tewari, Lingjie Liu, and Christian Theobalt · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Later among the works it cites.
3d-aware indoor scene synthesis with depth priors
Zifan Shi, Yujun Shen, Jiapeng Zhu, Dit-Yan Yeung, and Qifeng Chen · 2022
Later among the works it cites.
Volux-gan: A generative model for 3d face synthesis with hdri relighting
Feitong Tan, Sean Fanello, Abhimitra Meka, Sergio Orts-Escolano, Danhang Tang, Rohit Pandey, Jonathan Taylor, Ping Tan, and Yinda Zhang · 2022
Later among the works it cites.
High-fidelity GAN inversion for image attribute editing
Tengfei Wang, Yong Zhang, Yanbo Fan, Jue Wang, and Qifeng Chen · 2022
Later among the works it cites.
Zoedepth: Zero-shot transfer by combining relative and metric depth
Shariq Farooq Bhat, Reiner Birkl, Diana Wofk, Peter Wonka, and Matthias Müller · 2023
Closest in time.
Stylitgan: Prompting stylegan to generate new illumination conditions
Anand Bhattad and D.A. Forsyth · 2023
Closest in time.
Make it so: Steering stylegan for any image inversion and editing
Anand Bhattad, Viraj Shah, Derek Hoiem, and DA Forsyth · 2023
Closest in time.
Eva-02: A visual representation for neon genesis
Yuxin Fang, Quan Sun, Xinggang Wang, Tiejun Huang, Xinlong Wang, and Yue Cao · 2023
Closest in time.
Eva: Exploring the limits of masked visual representation learning at scale
Yuxin Fang, Wen Wang, Binhui Xie, Quan Sun, Ledell Wu, Xinggang Wang, Tiejun Huang, Xinlong Wang, and Yue Cao · 2023
Closest in time.
Scaling up gans for text-to-image synthesis
Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park, Eli Shechtman, Sylvain Paris, and Taesung Park · 2023
Closest in time.
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 · 2023
Closest in time.
Chong Mou, Xintao Wang, Liangbin Xie, Jian Zhang, Zhongang Qi, Ying Shan, and Xiaohu Qie · 2023
Closest in time.
Fake it till you make it: Learning transferable representations from synthetic imagenet clones
Mert Bulent Sariyildiz, Karteek Alahari, Diane Larlus, and Yannis Kalantidis · 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.
Adding conditional control to text-to-image diffusion models, 2023
Lvmin Zhang and Maneesh Agrawala · 2023
Closest in time.
Unleashing text-to-image diffusion models for visual perception
Wenliang Zhao, Yongming Rao, Zuyan Liu, Benlin Liu, Jie Zhou, and Jiwen Lu · 2023
Closest in time.