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Creating high-quality materials in computer graphics is a challenging and time-consuming task, which requires great expertise.
A computational approach to edge detection
John Canny · 1986
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Going deeper with convolutions. corr abs/1409.4842 (2014), 2014
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2014
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Reflectance modeling by neural texture synthesis
Miika Aittala, Timo Aila, and Jaakko Lehtinen · 2016
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Generating images with perceptual similarity metrics based on deep networks
Alexey Dosovitskiy and Thomas Brox · 2016
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Brdf representation and acquisition
Darya Guarnera, Giuseppe Claudio Guarnera, Abhijeet Ghosh, Cornelia Denk, and Mashhuda Glencross · 2016
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Unrolled generative adversarial networks
Luke Metz, Ben Poole, David Pfau, and Jascha Sohl-Dickstein · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Building machines that learn and think like people
Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, and Samuel J Gershman · 2017
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Modeling surface appearance from a single photograph using self-augmented convolutional neural networks
Xiao Li, Yue Dong, Pieter Peers, and Xin Tong · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
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Highlight-aware two-stream network for single-image svbrdf acquisition
Jie Guo, Shuichang Lai, Chengzhi Tao, Yuelong Cai, Lei Wang, Yanwen Guo, and Ling-Qi Yan · 2021
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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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Surfacenet: Adversarial svbrdf estimation from a single image
Giuseppe Vecchio, Simone Palazzo, and Concetto Spampinato · 2021
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Designing a practical degradation model for deep blind image super-resolution
Kai Zhang, Jingyun Liang, Luc Van Gool, and Radu Timofte · 2021
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Adversarial single-image svbrdf estimation with hybrid training
Xilong Zhou and Nima Khademi Kalantari · 2021
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Single-image svbrdf capture with a rendering-aware deep network
Valentin Deschaintre, Miika Aittala, Fredo Durand, George Drettakis, and Adrien Bousseau · 2018
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Materials for masses: Svbrdf acquisition with a single mobile phone image
Zhengqin Li, Kalyan Sunkavalli, and Manmohan Chandraker · 2018
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On the convergence properties of gan training
Lars Mescheder · 2018
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Flexible SVBRDF capture with a multi-image deep network
Valentin Deschaintre, Miika Aittala, Frédo Durand, George Drettakis, and Adrien Bousseau · 2019
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Deep inverse rendering for high-resolution svbrdf estimation from an arbitrary number of images
Duan Gao, Xiao Li, Yue Dong, Pieter Peers, Kun Xu, and Xin Tong · 2019
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Deep 3d capture: Geometry and reflectance from sparse multi-view images
Sai Bi, Zexiang Xu, Kalyan Sunkavalli, David Kriegman, and Ravi Ramamoorthi · 2020
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Semi-procedural textures using point process texture basis functions
Pascal Guehl, Rémi Allegre, J-M Dischler, Bedrich Benes, and Eric Galin · 2020
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Controlling material appearance by examples
Yiwei Hu, Miloš Hašan, Paul Guerrero, Holly Rushmeier, and Valentin Deschaintre · 2022
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Materia: Single image high-resolution material capture in the wild
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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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Midgard: A simulation platform for autonomous navigation in unstructured environments
Giuseppe Vecchio, Simone Palazzo, Dario C Guastella, Ignacio Carlucho, Stefano V Albrecht, Giovanni Muscato, and Concetto Spampinato · 2022
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TileGen: Tileable, controllable material generation and capture
Xilong Zhou, Milos Hasan, Valentin Deschaintre, Paul Guerrero, Kalyan Sunkavalli, and Nima Khademi Kalantari · 2022
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Text2Mat: Generating Materials from Text
Zhen He, Jie Guo, Yan Zhang, Qinghao Tu, Mufan Chen, Yanwen Guo, Pengyu Wang, and Wei Dai · 2023
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Composer: Creative and controllable image synthesis with composable conditions
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Infinite photorealistic worlds using procedural generation
Alexander Raistrick, Lahav Lipson, Zeyu Ma, Lingjie Mei, Mingzhe Wang, Yiming Zuo, Karhan Kayan, Hongyu Wen, Beining Han, Yihan Wang, Alejandro Newell, Hei Law, Ankit Goyal, Kaiyu Yang, and Jia Deng · 2023
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Synthetic datasets for autonomous driving: A survey, 2023
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Exploring clip for assessing the look and feel of images
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Adding conditional control to text-to-image diffusion models
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