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Vast amounts of artistic data is scattered on-line from both museums and art applications.
Acquiring a concept of painting style
Jean C Rush. 1979 · 1979
Earlier work this paper cites.
Iconclass: an iconographic classification system
Leendert D Couprie. 1983 · 1983
Earlier work this paper cites.
Multitask learning
Rich Caruana. 1998 · 1998
Earlier work this paper cites.
Industrial applications of X-ray diffraction
Frank H Chung and Deane K Smith. 1999 · 1999
Earlier work this paper cites.
Analysis of pigments and inks on oil paintings and historical manuscripts using total reflection x-ray fluorescence spectrometry
R Klockenkämper, A Von Bohlen, and Luc Moens. 2000 · 2000
Earlier work this paper cites.
Dutch Seventeenth-century Genre Painting: Its Stylistic and Thematic Evolution
W.E. Franits. 2004 · 2004
Earlier work this paper cites.
Toward a Geography of Art
T.D.C. Kaufmann. 2004 · 2004
Earlier work this paper cites.
LIBLINEAR: A library for large linear classification
Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, and Chih-Jen Lin. 2008 · 2008
Earlier work this paper cites.
Image processing for artist identification
C Richard Johnson, Ella Hendriks, Igor J Berezhnoy, Eugene Brevdo, Shannon M Hughes, Ingrid Daubechies, Jia Li, Eric Postma, and James Z Wang. 2008 · 2008
Earlier work this paper cites.
Semantic annotation and search of cultural-heritage collections: The MultimediaN E-Culture demonstrator
Guus Schreiber, Alia Amin, Lora Aroyo, Mark van Assem, Victor de Boer, Lynda Hardman, Michiel Hildebrand, Borys Omelayenko, Jacco van Osenbruggen, Anna Tordai, and others. 2008 · 2008
Earlier work this paper cites.
Memory of the Netherlands: Past and Future of the Dutch National Database on Cultural Heritage
Huibert Crijns and Anna Rademakers. 2009 · 2009
Earlier work this paper cites.
Rectified linear units improve restricted boltzmann machines. In Proceedings of the 27th international conference on machine learning (ICML-10)
Vinod Nair and Geoffrey E Hinton. 2010 · 2010
Earlier work this paper cites.
Combined regression and ranking. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
David Sculley. 2010 · 2010
Earlier work this paper cites.
Evaluating color descriptors for object and scene recognition
Koen Van De Sande, Theo Gevers, and Cees Snoek. 2010 · 2010
Earlier work this paper cites.
Academia meets industry at the Multimedia Grand Challenge
Cees GM Snoek and Malcolm Slaney. 2011 · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012 · 2012
Cited alongside, same era.
Efficient backprop
Yann A LeCun, Léon Bottou, Genevieve B Orr, and Klaus-Robert Müller. 2012 · 2012
Cited alongside, same era.
Sergey Karayev, Matthew Trentacoste, Helen Han, Aseem Agarwala, Trevor Darrell, Aaron Hertzmann, and Holger Winnemoeller. 2013 · 2013
Cited alongside, same era.
Classification of artistic styles using binarized features derived from a deep neural network. In Workshop at the European Conference on Computer Vision
Yaniv Bar, Noga Levy, and Lior Wolf. 2014 · 2014
Cited alongside, same era.
In search of art. In Workshop at the European Conference on Computer Vision
Elliot J Crowley and Andrew Zisserman. 2014 · 2014
Cited alongside, same era.
Toward Discovery of the Artist’s Style: Learning to recognize artists by their artworks
Nanne van Noord, Ella Hendriks, and Eric Postma. 2015 · 2015
Later among the works it cites.
Quantitative canvas weave analysis using 2-D synchrosqueezed transforms: Application of time-frequency analysis to art investigation
Haizhao Yang, Jianfeng Lu, William P Brown, Ingrid Daubechies, and Lexing Ying. 2015 · 2015
Later among the works it cites.
Image style transfer using convolutional neural networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
Leon A Gatys, Alexander S Ecker, and Matthias Bethge. 2016 · 2016
Later among the works it cites.
Convolutional sketch inversion. In European Conference on Computer Vision
Yağmur Güçlütürk, Umut Güçlü, Rob van Lier, and Marcel AJ van Gerven. 2016 · 2016
Later among the works it cites.
Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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Detecting people in cubist art. In Workshop at the European Conference on Computer Vision
Shiry Ginosar, Daniel Haas, Timothy Brown, and Jitendra Malik. 2014 · 2014
Cited alongside, same era.
The rijksmuseum challenge: Museum-centered visual recognition. In Proceedings of International Conference on Multimedia Retrieval
Thomas Mensink and Jan Van Gemert. 2014 · 2014
Cited alongside, same era.
EuropeanaTech Task Force on a Multilingual and Semantic Enrichment Strategy: final report
Agnès Simon, Bibliothèque Nationale de France, Daniel Vila Suero, Eero Hyvönen, Lars G Svensson, Deutsche Nationalbibliothek, Roxanne Wyns, LIBIS Seth van Hooland, Juliane Stiller, and Vivien Petras. 2014 · 2014
Cited alongside, same era.
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan and Andrew Zisserman. 2014 · 2014
Cited alongside, same era.
A unified perspective on multi-domain and multi-task learning
Yongxin Yang and Timothy M Hospedales. 2014 · 2014
Cited alongside, same era.
Quantifying Creativity in Art Networks
Ahmed Elgammal and Babak Saleh. 2015 · 2015
Cited alongside, same era.
Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval
Xiaodong Liu, Jianfeng Gao, Xiaodong He, Li Deng, Kevin Duh, and Ye-Yi Wang. 2015 · 2015
Cited alongside, same era.
Later among the works it cites.
Adaptive Visual Feedback Generation for Facial Expression Improvement with Multi-task Deep Neural Networks. In Proceedings of the 2016 ACM on Multimedia Conference
Takuhiro Kaneko, Kaoru Hiramatsu, and Kunio Kashino. 2016 · 2016
Later among the works it cites.
Iasonas Kokkinos. 2016 · 2016
Later among the works it cites.
Cross-stitch networks for multi-task learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
Ishan Misra, Abhinav Shrivastava, Abhinav Gupta, and Martial Hebert. 2016 · 2016
Later among the works it cites.
Transferring Neural Representations for Low-Dimensional Indexing of Maya Hieroglyphic Art
Edgar Roman-Rangel, Gulcan Can, Stephane Marchand-Maillet, Rui Hu, Carlos Pallán Gayol, Guido Krempel, Jakub Spotak, Jean-Marc Odobez, and Daniel Gatica-Perez. 2016 · 2016
Later among the works it cites.
Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning. In Proceedings of the 2016 ACM on Multimedia Conference
Keze Wang, Shengfu Zhai, Hui Cheng, Xiaodan Liang, and Liang Lin. 2016 · 2016
Later among the works it cites.
Detecting People in Artwork with CNNs. In European Conference on Computer Vision
Nicholas Westlake, Hongping Cai, and Peter Hall. 2016 · 2016
Later among the works it cites.
Multi-Task Zero-Shot Action Recognition with Prioritized Data Augmentation
Xun Xu, Timothy M. Hospedales, and Shaogang Gong. 2016 · 2016
Later among the works it cites.
Efficient Action Detection in Untrimmed Videos via Multi-Task Learning
Yi Zhu and Shawn D. Newsam. 2016 · 2016
Later among the works it cites.
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networkss
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros. 2017 · 2017
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