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This paper addresses cross-domain visual search, where visual queries retrieve category samples from a different domain.
Illumination for computer generated pictures
Bui Tuong Phong · 1975
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Database architecture for content-based image retrieval
Toshikazu Kato · 1992
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Fast multiresolution image querying
Charles E Jacobs, Adam Finkelstein, and David H Salesin · 1995
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The Princeton shape benchmark
Philip Shilane, Patrick Min, Michael Kazhdan, and Thomas Funkhouser · 2004
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Learning a similarity metric discriminatively, with application to face verification
Sumit Chopra, Raia Hadsell, and Yann LeCun · 2005
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Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun · 2006
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Diversifying search results
Rakesh Agrawal, Sreenivas Gollapudi, Alan Halverson, and Samuel Ieong · 2009
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Zero-shot learning with semantic output codes
Mark Palatucci, Dean Pomerleau, Geoffrey E Hinton, and Tom M Mitchell · 2009
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Distance metric learning for large margin nearest neighbor classification
Kilian Q Weinberger and Lawrence K Saul · 2009
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Sketch-based image retrieval: Benchmark and bag-of-features descriptors
Mathias Eitz, Kristian Hildebrand, Tamy Boubekeur, and Marc Alexa · 2010
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Software Framework for Topic Modelling with Large Corpora
Radim Řehůřek and Petr Sojka · 2010
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Generalizing from several related classification tasks to a new unlabeled sample
Gilles Blanchard, Gyemin Lee, and Clayton Scott · 2011
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A bag-of-regions approach to sketch-based image retrieval
Rui Hu, Tinghuai Wang, and John Collomosse · 2011
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How do humans sketch objects?
Mathias Eitz, James Hays, and Marc Alexa · 2012
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Iterative quantization: A procrustean approach to learning binary codes for large-scale image retrieval
Yunchao Gong, Svetlana Lazebnik, Albert Gordo, and Florent Perronnin · 2012
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Devise: A deep visual-semantic embedding model
Andrea Frome, Greg S Corrado, Jon Shlens, Samy Bengio, Jeff Dean, Marc’Aurelio Ranzato, and Tomas Mikolov · 2013
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A performance evaluation of gradient field hog descriptor for sketch based image retrieval
Rui Hu and John Collomosse · 2013
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Shrec’13 track: large scale sketch-based 3d shape retrieval
Bo Li, Yijuan Lu, Afzal Godil, Tobias Schreck, Masaki Aono, Henry Johan, Jose M Saavedra, and Shoki Tashiro · 2013
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Distance-based image classification: Generalizing to new classes at near-zero cost
Thomas Mensink, Jakob Verbeek, Florent Perronnin, and Gabriela Csurka · 2013
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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On the importance of initialization and momentum in deep learning
Ilya Sutskever, James Martens, George Dahl, and Geoffrey Hinton · 2013
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2014
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A comparison of methods for sketch-based 3d shape retrieval
Bo Li, Yijuan Lu, Afzal Godil, Tobias Schreck, Benjamin Bustos, Alfredo Ferreira, Takahiko Furuya, Manuel J Fonseca, Henry Johan, Takahiro Matsuda, et al · 2014
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Shrec’14 track: Extended large scale sketch-based 3d shape retrieval
Bo Li, Yijuan Lu, Chunyuan Li, Afzal Godil, Tobias Schreck, Masaki Aono, Martin Burtscher, Hongbo Fu, Takahiko Furuya, Henry Johan, et al · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning · 2014
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Sketch based image retrieval using a soft computation of the histogram of edge local orientations (s-helo)
Jose M Saavedra · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin · 2015
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Multi-view convolutional neural networks for 3d shape recognition
Hang Su, Subhransu Maji, Evangelos Kalogerakis, and Erik G. Learned-Miller · 2015
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Sketch-based 3d shape retrieval using convolutional neural networks
Fang Wang, Le Kang, and Yi Li · 2015
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Domain-adversarial training of neural networks
Sketching out the details: Sketch-based image retrieval using convolutional neural networks with multi-stage regression
Tu Bui, Leonardo Ribeiro, Moacir Ponti, and John Collomosse · 2018
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Deep cross-modality adaptation via semantics preserving adversarial learning for sketch-based 3d shape retrieval
Jiaxin Chen and Yi Fang · 2018
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Image-to-image translation for cross-domain disentanglement
Abel Gonzalez-Garcia, Joost van de Weijer, and Yoshua Bengio · 2018
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Sketch-a-classifier: sketch-based photo classifier generation
Conghui Hu, Da Li, Yi-Zhe Song, Tao Xiang, and Timothy M Hospedales · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Learning large euclidean margin for sketch-based image retrieval
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Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
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Sketch-based image retrieval via siamese convolutional neural network
Yonggang Qi, Yi-Zhe Song, Honggang Zhang, and Jun Liu · 2016
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The sketchy database: Learning to retrieve badly drawn bunnies
Patsorn Sangkloy, Nathan Burnell, Cusuh Ham, and James Hays · 2016
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Improved deep metric learning with multi-class n-pair loss objective
Kihyuk Sohn · 2016
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Shape2vec: Semantic-based descriptors for 3d shapes, sketches and images
Flora Ponjou Tasse and Neil Dodgson · 2016
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A discriminative feature learning approach for deep face recognition
Yandong Wen, Kaipeng Zhang, Zhifeng Li, and Yu Qiao · 2016
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Sketchnet: Sketch classification with web images
Hua Zhang, Si Liu, Changqing Zhang, Wenqi Ren, Rui Wang, and Xiaochun Cao · 2016
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Peng Lu, Gao Huang, Yanwei Fu, Guodong Guo, and Hangyu Lin · 2018
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Semantic embedding for sketch-based 3d shape retrieval
Anran Qi, Yi-Zhe Song, and Tao Xiang · 2018
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Meta-learning for semi-supervised few-shot classification
Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B Tenenbaum, Hugo Larochelle, and Richard S Zemel · 2018
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Zero-shot sketch-image hashing
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Cosface: Large margin cosine loss for deep face recognition
Hao Wang, Yitong Wang, Zheng Zhou, Xing Ji, Dihong Gong, Jingchao Zhou, Zhifeng Li, and Wei Liu · 2018
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Zero-shot learning-a comprehensive evaluation of the good, the bad and the ugly
Yongqin Xian, Christoph H Lampert, Bernt Schiele, and Zeynep Akata · 2018
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Deep cocktail network: Multi-source unsupervised domain adaptation with category shift
Ruijia Xu, Ziliang Chen, Wangmeng Zuo, Junjie Yan, and Liang Lin · 2018
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A zero-shot framework for sketch based image retrieval
Sasi Kiran Yelamarthi, Shiva Krishna Reddy, Ashish Mishra, and Anurag Mittal · 2018
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Domain generalization by solving jigsaw puzzles
Fabio M Carlucci, Antonio D’Innocente, Silvia Bucci, Barbara Caputo, and Tatiana Tommasi · 2019
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Deep sketch-shape hashing with segmented 3d stochastic viewing
Jiaxin Chen, Jie Qin, Li Liu, Fan Zhu, Fumin Shen, Jin Xie, and Ling Shao · 2019
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Arcface: Additive angular margin loss for deep face recognition
Jiankang Deng, Jia Guo, Niannan Xue, and Stefanos Zafeiriou · 2019
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Doodle to search: Practical zero-shot sketch-based image retrieval
Sounak Dey, Pau Riba, Anjan Dutta, Josep Llados, and Yi-Zhe Song · 2019
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Domain generalization via model-agnostic learning of semantic features
Qi Dou, Daniel C Castro, Konstantinos Kamnitsas, and Ben Glocker · 2019
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Semantically tied paired cycle consistency for zero-shot sketch-based image retrieval
Anjan Dutta and Zeynep Akata · 2019
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Style-guided zero-shot sketch-based image retrieval
Titir Dutta and Soma Biswas · 2019
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Semantic-aware knowledge preservation for zero-shot sketch-based image retrieval
Qing Liu, Lingxi Xie, Huiyu Wang, and Alan Yuille · 2019
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Hyperspherical prototype networks
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Moment matching for multi-source domain adaptation
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