Fetching the paper…
Reading the bibliography…
Generative models are now widely used by graphic designers and artists.
The senses considered as perceptual systems
James Jerome Gibson · 1966
Earlier work this paper cites.
Separating style and content
Joshua Tenenbaum and William Freeman · 1996
Earlier work this paper cites.
Hierarchical classification of paintings using face-and brush stroke models
Robert Sablatnig, Paul Kammerer, and Ernestine Zolda · 1998
Earlier work this paper cites.
The art and science of portraiture
Sara Lawrence-Lightfoot and Jessica Hoffmann Davis · 2002
Earlier work this paper cites.
Learning a similarity metric discriminatively, with application to face verification
Sumit Chopra, Raia Hadsell, and Yann LeCun · 2005
Earlier work this paper cites.
Defining pictorial style: Lessons from linguistics and computer graphics
John Willats and Frédo Durand · 2005
Earlier work this paper cites.
Characterizing elegance of curves computationally for distinguishing morrisseau paintings and the imitations
Lei Yao, Jia Li, and James Z Wang · 2009
Earlier work this paper cites.
Stylometrics of artwork: uses and limitations
James M Hughes, Daniel J Graham, and Daniel N Rockmore · 2010
Earlier work this paper cites.
Comparing higher-order spatial statistics and perceptual judgements in the stylometric analysis of art
James M Hughes, Daniel J Graham, C Robert Jacobsen, and Daniel N Rockmore · 2011
Earlier work this paper cites.
Rhythmic brushstrokes distinguish van gogh from his contemporaries: findings via automated brushstroke extraction
Jia Li, Lei Yao, Ella Hendriks, and James Z Wang · 2011
Earlier work this paper cites.
Statistics, vision, and the analysis of artistic style
Daniel J Graham, James M Hughes, Helmut Leder, and Daniel N Rockmore · 2012
Earlier work this paper cites.
Sergey Karayev, Matthew Trentacoste, Helen Han, Aseem Agarwala, Trevor Darrell, Aaron Hertzmann, and Holger Winnemoeller · 2013
Earlier work this paper cites.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
Earlier work this paper cites.
Style transfer via image component analysis
Wei Zhang, Chen Cao, Shifeng Chen, Jianzhuang Liu, and Xiaoou Tang · 2013
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
Earlier work this paper cites.
Genre and style based painting classification
Siddharth Agarwal, Harish Karnick, Nirmal Pant, and Urvesh Patel · 2015
Earlier work this paper cites.
A neural algorithm of artistic style
Leon A Gatys, Alexander S Ecker, and Matthias Bethge · 2015
Earlier work this paper cites.
Deep multi-patch aggregation network for image style, aesthetics, and quality estimation
Xin Lu, Zhe Lin, Xiaohui Shen, Radomir Mech, and James Z Wang · 2015
Earlier work this paper cites.
Elements of style: learning perceptual shape style similarity
Zhaoliang Lun, Evangelos Kalogerakis, and Alla Sheffer · 2015
Earlier work this paper cites.
Large-scale classification of fine-art paintings: Learning the right metric on the right feature
Babak Saleh and Ahmed Elgammal · 2015
Earlier work this paper cites.
Netvlad: Cnn architecture for weakly supervised place recognition
Relja Arandjelovic, Petr Gronat, Akihiko Torii, Tomas Pajdla, and Josef Sivic · 2016
Earlier work this paper cites.
A learned representation for artistic style
Vincent Dumoulin, Jonathon Shlens, and Manjunath Kudlur · 2016
Earlier work this paper cites.
Image style transfer using convolutional neural networks
Leon A Gatys, Alexander S Ecker, and Matthias Bethge · 2016
Cited alongside, same era.
Cnn-based style vector for style image retrieval
Shin Matsuo and Keiji Yanai · 2016
Cited alongside, same era.
Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
Cited alongside, same era.
Recognizing art style automatically in painting with deep learning
Adrian Lecoutre, Benjamin Negrevergne, and Florian Yger · 2017
Cited alongside, same era.
Deep photo style transfer
Fujun Luan, Sylvain Paris, Eli Shechtman, and Kavita Bala · 2017
Cited alongside, same era.
Bam! the behance artistic media dataset for recognition beyond photography
Michael J Wilber, Chen Fang, Hailin Jin, Aaron Hertzmann, John Collomosse, and Serge Belongie · 2017
Cited alongside, same era.
Frozen in time: A joint video and image encoder for end-to-end retrieval
Max Bain, Arsha Nagrani, Gül Varol, and Andrew Zisserman · 2021
Later among the works it cites.
Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
Later among the works it cites.
Cosmo: Content-style modulation for image retrieval with text feedback
Seungmin Lee, Dongwan Kim, and Bohyung Han · 2021
Later among the works it 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, et al · 2021
Later among the works it cites.
Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Image style classification based on learnt deep correlation features
Wei-Ta Chu and Yi-Ling Wu · 2018
Cited alongside, same era.
How to read paintings: semantic art understanding with multi-modal retrieval
Noa Garcia and George Vogiatzis · 2018
Cited alongside, same era.
Multimodal unsupervised image-to-image translation
Xun Huang, Ming-Yu Liu, Serge Belongie, and Jan Kautz · 2018
Cited alongside, same era.
Classification of style in fine-art paintings using transfer learning and weighted image patches
Catherine Sandoval Rodriguez, Margaret Lech, and Elena Pirogova · 2018
Cited alongside, same era.
Unsupervised learning of artistic styles with archetypal style analysis
Daan Wynen, Cordelia Schmid, and Julien Mairal · 2018
Cited alongside, same era.
Svd: A large-scale short video dataset for near-duplicate video retrieval
Qing-Yuan Jiang, Yi He, Gen Li, Jian Lin, Lei Li, and Wu-Jun Li · 2019
Cited alongside, same era.
Dan Ruta, Saeid Motiian, Baldo Faieta, Zhe Lin, Hailin Jin, Alex Filipkowski, Andrew Gilbert, and John Collomosse · 2021
Later among the works it cites.
Automatic analysis of artistic paintings using information-based measures
Jorge Miguel Silva, Diogo Pratas, Rui Antunes, Sérgio Matos, and Armando J Pinho · 2021
Later among the works it cites.
Jonas Geiping, Micah Goldblum, Gowthami Somepalli, Ravid Shwartz-Ziv, Tom Goldstein, and Andrew Gordon Wilson · 2022
Later among the works it cites.
A self-supervised descriptor for image copy detection
Ed Pizzi, Sreya Dutta Roy, Sugosh Nagavara Ravindra, Priya Goyal, and Matthijs Douze · 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.
Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
Later among the works it cites.
Wikiartvectors: style and color representations of artworks for cultural analysis via information theoretic measures
Bhargav Srinivasa Desikan, Hajime Shimao, and Helena Miton · 2022
Later among the works it cites.
Fine-grained image style transfer with visual transformers
Jianbo Wang, Huan Yang, Jianlong Fu, Toshihiko Yamasaki, and Baining Guo · 2022
Later among the works it cites.
Firefly, 2023
Adobe · 2023
Later among the works it cites.
A cookbook of self-supervised learning
Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Gregoire Mialon, Yuandong Tian, et al · 2023
Later among the works it cites.
Improving image generation with better captions
James Betker, Gabriel Goh, Li Jing, Tim Brooks, Jianfeng Wang, Linjie Li, Long Ouyang, Juntang Zhuang, Joyce Lee, Yufei Guo, et al · 2023
Later among the works it cites.
Würstchen: An efficient architecture for large-scale text-to-image diffusion models
Pablo Pernias, Dominic Rampas, Mats Leon Richter, Christopher Pal, and Marc Aubreville · 2023
Later among the works it cites.
Clip interrogator
pharmapsychotic · 2023
Later among the works it cites.
Teaching matters: Investigating the role of supervision in vision transformers
Matthew Walmer, Saksham Suri, Kamal Gupta, and Abhinav Shrivastava · 2023
Later among the works it cites.
Evaluating data attribution for text-to-image models
Sheng-Yu Wang, Alexei A Efros, Jun-Yan Zhu, and Richard Zhang · 2023
Later among the works it cites.
Greg rutkowski removed from stable diffusion but brought back by ai artists, March 2024
Decrypt · 2024
Closest in time.