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Free-hand sketches are highly illustrative, and have been widely used by humans to depict objects or stories from ancient times to the present.
I. E. Sutherland, “Sketchpad a man-machine graphical communication system,” Simulation , 1964
1964
Earlier work this paper cites.
C. F. Herot, “Graphical input through machine recognition of sketches,” TOG , 1976
1976
Earlier work this paper cites.
J. Canny, “A computational approach to edge detection,” TPAMI , 1986
1986
Earlier work this paper cites.
T. Kato, T. Kurita, N. Otsu, and K. Hirata, “A sketch retrieval method for full color image database-query by visual example,” in ICPR , 1992
1992
Earlier work this paper cites.
C. Cortes and V. Vapnik, “Support-vector networks,” Machine learning , 1995
1995
Earlier work this paper cites.
M. Schuster and K. K. Paliwal, “Bidirectional recurrent neural networks,” TSP , 1997
1997
Earlier work this paper cites.
Y.-P. Tan, S. R. Kulkarni, and P. J. Ramadge, “A framework for measuring video similarity and its application to video query by example,” in ICIP , 1999
1999
Earlier work this paper cites.
D. DeCarlo, A. Finkelstein, S. Rusinkiewicz, and A. Santella, “Suggestive contours for conveying shape,” TOG , 2003
2003
Earlier work this paper cites.
D. G. Lowe, “Distinctive image features from scale-invariant keypoints,” IJCV , 2004
2004
Earlier work this paper cites.
G. Hinton and V. Nair, “Inferring motor programs from images of handwritten digits,” in NeurIPS , 2005
2005
Earlier work this paper cites.
P. Barla, J. Thollot, and F. X. Sillion, “Geometric clustering for line drawing simplification,” in TOG , 2005
2005
Earlier work this paper cites.
S. Chopra, R. Hadsell, Y. LeCun et al. , “Learning a similarity metric discriminatively, with application to face verification,” in CVPR , 2005
2005
Earlier work this paper cites.
X. Hilaire and K. Tombre, “Robust and accurate vectorization of line drawings,” TPAMI , 2006
2006
Earlier work this paper cites.
J. P. Collomosse, G. McNeill, and L. Watts, “Free-hand sketch grouping for video retrieval,” in ICPR , 2008
2008
Earlier work this paper cites.
B. Paulson and T. Hammond, “Paleosketch: accurate primitive sketch recognition and beautification,” in Proceedings of the 13th international conference on Intelligent user interfaces , 2008, pp. 1–10
2008
Earlier work this paper cites.
J. P. Collomosse, G. McNeill, and Y. Qian, “Storyboard sketches for content based video retrieval,” in ICCV , 2009
2009
Earlier work this paper cites.
D. Sỳkora, J. Dingliana, and S. Collins, “Lazybrush: Flexible painting tool for hand-drawn cartoons,” in Computer Graphics Forum , 2009
2009
Earlier work this paper cites.
T. Shao, W. Xu, K. Yin, J. Wang, K. Zhou, and B. Guo, “Discriminative sketch-based 3d model retrieval via robust shape matching,” in Computer Graphics Forum , 2011
2011
Earlier work this paper cites.
D. Sỳkora, M. Ben-Chen, M. Čadík, B. Whited, and M. Simmons, “Textoons: practical texture mapping for hand-drawn cartoon animations,” in Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Non-Photorealistic Animation and Rendering , 2011
2011
Earlier work this paper cites.
M. Eitz, J. Hays, and M. Alexa, “How do humans sketch objects?” TOG , 2012
2012
Earlier work this paper cites.
C. Tirkaz, B. Yanikoglu, and T. M. Sezgin, “Sketched symbol recognition with auto-completion,” PR , 2012
2012
Earlier work this paper cites.
M. Eitz, R. Richter, T. Boubekeur, K. Hildebrand, and M. Alexa, “Sketch-based shape retrieval,” TOG , 2012
2012
Earlier work this paper cites.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in NeurIPS , 2012
2012
Earlier work this paper cites.
D. Chen, X. Cao, L. Wang, F. Wen, and J. Sun, “Bayesian face revisited: A joint formulation,” in ECCV , 2012
2012
Earlier work this paper cites.
R. O. Duda, P. E. Hart, and D. G. Stork, Pattern classification . John Wiley & Sons, 2012
2012
Earlier work this paper cites.
J. Wagemans, J. H. Elder, M. Kubovy, S. E. Palmer, M. A. Peterson, M. Singh, and R. von der Heydt, “A century of gestalt psychology in visual perception: I. perceptual grouping and figure–ground organization.” Psychological bulletin , 2012
2012
Earlier work this paper cites.
Z. Sun, C. Wang, L. Zhang, and L. Zhang, “Free hand-drawn sketch segmentation,” in ECCV , 2012
2012
Earlier work this paper cites.
V. I. Bogachev and A. V. Kolesnikov, “The monge-kantorovich problem: achievements, connections, and perspectives,” Russian Mathematical Surveys , 2012
2012
Earlier work this paper cites.
R. Hu and J. Collomosse, “A performance evaluation of gradient field hog descriptor for sketch based image retrieval,” CVIU , 2013
2013
Earlier work this paper cites.
2013
Earlier work this paper cites.
K. Koffka, Principles of Gestalt psychology . Routledge, 2013
2013
Earlier work this paper cites.
G. Andrew, R. Arora, J. Bilmes, and K. Livescu, “Deep canonical correlation analysis,” in ICML , 2013
2013
Earlier work this paper cites.
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean, “Distributed representations of words and phrases and their compositionality,” in NeurIPS , 2013
2013
Earlier work this paper cites.
C. H. Lampert, H. Nickisch, and S. Harmeling, “Attribute-based classification for zero-shot visual object categorization,” TPAMI , 2013
2013
Earlier work this paper cites.
B. Li, Y. Lu, A. Godil, T. Schreck, B. Bustos, A. Ferreira, T. Furuya, M. J. Fonseca, H. Johan, T. Matsuda et al. , “A comparison of methods for sketch-based 3d shape retrieval,” CVIU , 2014
2014
Earlier work this paper cites.
B. Li, Y. Lu, C. Li, A. Godil, T. Schreck, M. Aono, M. Burtscher, H. Fu, T. Furuya, H. Johan et al. , “Shrec’14 track: Extended large scale sketch-based 3d shape retrieval,” in Eurographics workshop on 3D object retrieval , 2014
2014
Earlier work this paper cites.
Y. Li, T. M. Hospedales, Y.-Z. Song, and S. Gong, “Fine-grained sketch-based image retrieval by matching deformable part models,” in BMVC , 2014
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in NeurIPS , 2014
2014
Earlier work this paper cites.
Z. Huang, H. Fu, and R. W. Lau, “Data-driven segmentation and labeling of freehand sketches,” TOG , 2014
2014
Earlier work this paper cites.
Y. Chien, W.-C. Lin, T.-S. Huang, and J.-H. Chuang, “Line drawing simplification by stroke translation and combination,” in ICGIP , 2014
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
B. Graham, “Spatially-sparse convolutional neural networks,” arXiv preprint arXiv:1409.6070 , 2014
2014
Earlier work this paper cites.
Y. Li, T. M. Hospedales, Y.-Z. Song, and S. Gong, “Fine-grained sketch-based image retrieval by matching deformable part models,” in BMVC , 2014
2014
Earlier work this paper cites.
S.-i. Kondo, M. Toyoura, and X. Mao, “Sketch based skirt image retrieval,” in Proceedings of the 4th Joint Symposium on Computational Aesthetics, Non-Photorealistic Animation and Rendering, and Sketch-Based Interfaces and Modeling , 2014
2014
Earlier work this paper cites.
C. L. Zitnick and P. Dollár, “Edge boxes: Locating object proposals from edges,” in ECCV , 2014
2014
Earlier work this paper cites.
2014
Earlier work this paper cites.
F. Wang, L. Kang, and Y. Li, “Sketch-based 3d shape retrieval using convolutional neural networks,” in CVPR , 2015
2015
Earlier work this paper cites.
Q. Yu, Y. Yang, Y.-Z. Song, T. Xiang, and T. M. Hospedales, “Sketch-a-net that beats humans,” in BMVC , 2015
2015
Earlier work this paper cites.
M. R. Amer, S. Yousefi, R. Raich, and S. Todorovic, “Monocular extraction of 2.1 d sketch using constrained convex optimization,” IJCV , 2015
2015
Earlier work this paper cites.
N. Prajapati and G. Prajapti, “Sketch based image retrieval system for the web-a survey,” IJCSIT , 2015
2015
Earlier work this paper cites.
F. Schroff, D. Kalenichenko, and J. Philbin, “Facenet: A unified embedding for face recognition and clustering,” in CVPR , 2015
2015
Earlier work this paper cites.
C. Xiao, C. Wang, L. Zhang, and L. Zhang, “Sketch-based image retrieval via shape words,” in ICMR , 2015
2015
Earlier work this paper cites.
O. Seddati, S. Dupont, and S. Mahmoudi, “Deepsketch: deep convolutional neural networks for sketch recognition and similarity search,” in CBMI , 2015
2015
Earlier work this paper cites.
F. Wang and Y. Li, “Spatial matching of sketches without point correspondence,” in ICIP , 2015
2015
Earlier work this paper cites.
Y. Qi, J. Guo, Y.-Z. Song, T. Xiang, H. Zhang, and Z.-H. Tan, “Im2sketch: Sketch generation by unconflicted perceptual grouping,” Neurocomputing , 2015
2015
Earlier work this paper cites.
Y. Qi, Y.-Z. Song, T. Xiang, H. Zhang, T. Hospedales, Y. Li, and J. Guo, “Making better use of edges via perceptual grouping,” in CVPR , 2015
2015
Earlier work this paper cites.
X. Liu, T.-T. Wong, and P.-A. Heng, “Closure-aware sketch simplification,” TOG , 2015
2015
Earlier work this paper cites.
J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation,” in CVPR , 2015
2015
Earlier work this paper cites.
R. K. Sarvadevabhatla et al. , “Eye of the dragon: Exploring discriminatively minimalist sketch-based abstractions for object categories,” in MM , 2015
2015
Earlier work this paper cites.
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei, “Imagenet large scale visual recognition challenge,” IJCV , 2015
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
Y. Matsui, “Challenge for manga processing: Sketch-based manga retrieval,” in MM , 2015
2015
Earlier work this paper cites.
S. Xie and Z. Tu, “Holistically-nested edge detection,” in ICCV , 2015
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
K. Lin, H.-F. Yang, J.-H. Hsiao, and C.-S. Chen, “Deep learning of binary hash codes for fast image retrieval,” in CVPR Workshops , 2015
2015
Earlier work this paper cites.
Y. Fu, T. M. Hospedales, T. Xiang, and S. Gong, “Transductive multi-view zero-shot learning,” TPAMI , 2015
2015
Earlier work this paper cites.
J. C. Roberts, C. Headleand, and P. D. Ritsos, “Sketching designs using the five design-sheet methodology,” TVCG , 2015
2015
Earlier work this paper cites.
Q. Yu, F. Liu, Y.-Z. Song, T. Xiang, T. M. Hospedales, and C.-C. Loy, “Sketch me that shoe,” in CVPR , 2016
2016
Earlier work this paper cites.
P. Sangkloy, N. Burnell, C. Ham, and J. Hays, “The sketchy database: learning to retrieve badly drawn bunnies,” TOG , 2016
2016
Earlier work this paper cites.
E. Simo-Serra, S. Iizuka, K. Sasaki, and H. Ishikawa, “Learning to simplify: fully convolutional networks for rough sketch cleanup,” TOG , 2016
2016
Earlier work this paper cites.
S. Ouyang, T. M. Hospedales, Y.-Z. Song, and X. Li, “Forgetmenot: Memory-aware forensic facial sketch matching,” in CVPR , 2016
2016
Earlier work this paper cites.
M. Indu and K. Kavitha, “Survey on sketch based image retrieval methods,” in ICCPCT , 2016
2016
Earlier work this paper cites.
H. Zhang, S. Liu, C. Zhang, W. Ren, R. Wang, and X. Cao, “Sketchnet: Sketch classification with web images,” in CVPR , 2016
2016
Earlier work this paper cites.
X. Wang, X. Duan, and X. Bai, “Deep sketch feature for cross-domain image retrieval,” Neurocomputing , 2016
2016
Earlier work this paper cites.
L. Castrejon, Y. Aytar, C. Vondrick, H. Pirsiavash, and A. Torralba, “Learning aligned cross-modal representations from weakly aligned data,” in CVPR , 2016
2016
Earlier work this paper cites.
Y. Matsui, T. Shiratori, and K. Aizawa, “Drawfromdrawings: 2d drawing assistance via stroke interpolation with a sketch database,” TVCG , 2016
2016
Earlier work this paper cites.
Y. Ye, Y. Lu, and H. Jiang, “Human’s scene sketch understanding,” in ICMR , 2016
2016
Earlier work this paper cites.
Y. Zhang, Y. Zhang, and X. Qian, “Deep neural networks for free-hand sketch recognition,” in Pacific Rim Conference on Multimedia , 2016
2016
Earlier work this paper cites.
J. Guo, C. Wang, E. Roman-Rangel, H. Chao, and Y. Rui, “Building hierarchical representations for oracle character and sketch recognition,” TIP , 2016
2016
Earlier work this paper cites.
P. Ballester and R. M. Araujo, “On the performance of googlenet and alexnet applied to sketches,” in AAAI , 2016
2016
Earlier work this paper cites.
O. Seddati, S. Dupont, and S. Mahmoudi, “Deepsketch 2: Deep convolutional neural networks for partial sketch recognition,” in CBMI , 2016
2016
Earlier work this paper cites.
O. Seddati, S. Dupont, and S. Mahmoudi, “Deepsketch2image: deep convolutional neural networks for partial sketch recognition and image retrieval,” in MM , 2016
2016
Earlier work this paper cites.
R. K. Sarvadevabhatla, J. Kundu et al. , “Enabling my robot to play pictionary: Recurrent neural networks for sketch recognition,” in MM , 2016
2016
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in CVPR , 2016
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
A. Creswell and A. A. Bharath, “Adversarial training for sketch retrieval,” in ECCV , 2016
2016
Earlier work this paper cites.
R. G. Schneider and T. Tuytelaars, “Example-based sketch segmentation and labeling using crfs,” TOG , 2016
2016
Earlier work this paper cites.
L. Yi, V. G. Kim, D. Ceylan, I. Shen, M. Yan, H. Su, C. Lu, Q. Huang, A. Sheffer, L. Guibas et al. , “A scalable active framework for region annotation in 3d shape collections,” TOG , 2016
2016
Earlier work this paper cites.
T. Ogawa, Y. Matsui, T. Yamasaki, and K. Aizawa, “Sketch simplification by classifying strokes,” in ICPR , 2016
2016
Earlier work this paper cites.
P. Xu, K. Li, Z. Ma, Y.-Z. Song, L. Wang, and J. Guo, “Cross-modal subspace learning for sketch-based image retrieval: A comparative study,” in IC-NIDC , 2016
2016
Earlier work this paper cites.
S. D. Bhattacharjee, J. Yuan, W. Hong, and X. Ruan, “Query adaptive instance search using object sketches,” in MM , 2016
2016
Earlier work this paper cites.
P. Xu, Q. Yin, Y. Qi, Y.-Z. Song, Z. Ma, L. Wang, and J. Guo, “Instance-level coupled subspace learning for fine-grained sketch-based image retrieval,” in ECCV Workshops , 2016
2016
Earlier work this paper cites.
Y. Qi, Y.-Z. Song, H. Zhang, and J. Liu, “Sketch-based image retrieval via siamese convolutional neural network,” in ICIP , 2016
2016
Earlier work this paper cites.
J. Song, Y.-Z. Song, T. Xiang, T. M. Hospedales, and X. Ruan, “Deep multi-task attribute-driven ranking for fine-grained sketch-based image retrieval.” in BMVC , 2016
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
B. Li, Y. Lu, and J. Shen, “A semantic tree-based approach for sketch-based 3d model retrieval,” in ICPR , 2016
2016
Earlier work this paper cites.
F. Zhu, J. Xie, and Y. Fang, “Learning cross-domain neural networks for sketch-based 3d shape retrieval,” in AAAI , 2016
2016
Earlier work this paper cites.
Y. Ye, B. Li, and Y. Lu, “3d sketch-based 3d model retrieval with convolutional neural network,” in ICPR , 2016
2016
Earlier work this paper cites.
H. Huang, E. Kalogerakis, E. Yumer, and R. Mech, “Shape synthesis from sketches via procedural models and convolutional networks,” TVCG , 2016
2016
Earlier work this paper cites.
S. Wu, H. Su, S. Zheng, H. Yang, and Q. Zhou, “Motion sketch based crowd video retrieval via motion structure coding,” in ICIP , 2016
2016
Earlier work this paper cites.
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna, “Rethinking the inception architecture for computer vision,” in CVPR , 2016
2016
Earlier work this paper cites.
J.-D. Favreau, F. Lafarge, and A. Bousseau, “Fidelity vs. simplicity: a global approach to line drawing vectorization,” TOG , 2016
2016
Earlier work this paper cites.
B. Jackson and D. F. Keefe, “Lift-off: Using reference imagery and freehand sketching to create 3d models in vr,” TVCG , 2016
2016
Earlier work this paper cites.
F. Boniardi, A. Valada, W. Burgard, and G. D. Tipaldi, “Autonomous indoor robot navigation using a sketch interface for drawing maps and routes,” in ICRA , 2016
2016
Earlier work this paper cites.
Q. Yu, Y. Yang, F. Liu, Y.-Z. Song, T. Xiang, and T. M. Hospedales, “Sketch-a-net: A deep neural network that beats humans,” IJCV , 2017
2017
Earlier work this paper cites.
J. Song, Q. Yu, Y.-Z. Song, T. Xiang, and T. M. Hospedales, “Deep spatial-semantic attention for fine-grained sketch-based image retrieval,” in ICCV , 2017
2017
Earlier work this paper cites.
C. Hu, D. Li, Y.-Z. Song, and T. M. Hospedales, “Now you see me: Deep face hallucination for unviewed sketches.” in BMVC , 2017
2017
Earlier work this paper cites.
S. Nagpal, M. Singh, R. Singh, M. Vatsa, A. Noore, and A. Majumdar, “Face sketch matching via coupled deep transform learning,” in ICCV , 2017
2017
Earlier work this paper cites.
P. Sangkloy, J. Lu, C. Fang, F. Yu, and J. Hays, “Scribbler: Controlling deep image synthesis with sketch and color,” in CVPR , 2017
2017
Earlier work this paper cites.
R. K. Sarvadevabhatla, S. Suresh, and R. V. Babu, “Object category understanding via eye fixations on freehand sketches,” TIP , 2017
2017
Earlier work this paper cites.
T. Jiang, G.-S. Xia, and Q. Lu, “Sketch-based aerial image retrieval,” in ICIP , 2017
2017
Earlier work this paper cites.
T.-B. Jiang, G.-S. Xia, Q.-K. Lu, and W.-M. Shen, “Retrieving aerial scene images with learned deep image-sketch features,” JCST , 2017
2017
Earlier work this paper cites.
D. Li, Y. Yang, Y.-Z. Song, and T. M. Hospedales, “Deeper, broader and artier domain generalization,” in ICCV , 2017
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
J.-Y. He, X. Wu, Y.-G. Jiang, B. Zhao, and Q. Peng, “Sketch recognition with deep visual-sequential fusion model,” in MM , 2017
2017
Earlier work this paper cites.
Y. Li, Y.-Z. Song, T. M. Hospedales, and S. Gong, “Free-hand sketch synthesis with deformable stroke models,” IJCV , 2017
2017
Cited alongside, same era.
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille, “Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,” TPAMI , 2017
2017
Cited alongside, same era.
C. Wang, B. Yang, and Y. Liao, “Unsupervised image segmentation using convolutional autoencoder with total variation regularization as preprocessing,” in ICASSP , 2017
2017
Cited alongside, same era.
L. Donati, S. Cesano, and A. Prati, “An accurate system for fashion hand-drawn sketches vectorization,” in ICCV Workshops , 2017
2017
Cited alongside, same era.
R. K. Sarvadevabhatla, I. Dwivedi, A. Biswas, S. Manocha et al. , “Sketchparse: Towards rich descriptions for poorly drawn sketches using multi-task hierarchical deep networks,” in MM , 2017
S. Barocas, M. Hardt, and A. Narayanan, Fairness and Machine Learning . fairmlbook.org, 2019, http://www.fairmlbook.org
2019
Later among the works it cites.
2019
Later among the works it cites.
H. Zhang, P. She, Y. Liu, J. Gan, X. Cao, and H. Foroosh, “Learning structural representations via dynamic object landmarks discovery for sketch recognition and retrieval,” TIP , 2019
2019
Later among the works it cites.
K. Zhang, W. Luo, L. Ma, and H. Li, “Cousin network guided sketch recognition via latent attribute warehouse,” in AAAI , 2019
2019
Later among the works it cites.
F. Liu, X. Deng, Y.-K. Lai, Y.-J. Liu, C. Ma, and H. Wang, “Sketchgan: Joint sketch completion and recognition with generative adversarial network,” in CVPR , 2019
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2017
Cited alongside, same era.
L. Zheng, Y. Yang, and Q. Tian, “Sift meets cnn: A decade survey of instance retrieval,” TPAMI , 2017
2017
Cited alongside, same era.
J. Lei, K. Zheng, H. Zhang, X. Cao, N. Ling, and Y. Hou, “Sketch based image retrieval via image-aided cross domain learning,” in ICIP , 2017
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Y. Yan, X. Wang, X. Yang, X. Bai, and W. Liu, “Joint classification loss and histogram loss for sketch-based image retrieval,” in ICIG , 2017
2017
Cited alongside, same era.
J. Collomosse, T. Bui, M. J. Wilber, C. Fang, and H. Jin, “Sketching with style: Visual search with sketches and aesthetic context,” in ICCV , 2017
2017
Cited alongside, same era.
J. Song, Y.-Z. Song, T. Xiang, and T. M. Hospedales, “Fine-grained image retrieval: the text/sketch input dilemma,” in BMVC , 2017
2017
Cited alongside, same era.
F. Huang, Y. Cheng, C. Jin, Y. Zhang, and T. Zhang, “Deep multimodal embedding model for fine-grained sketch-based image retrieval,” in SIGIR , 2017
2017
Cited alongside, same era.
2019
Later among the works it cites.
2019
Later among the works it cites.
K. Sasaki and T. Ogata, “Adaptive drawing behavior by visuomotor learning using recurrent neural networks,” IEEE Transactions on Cognitive and Developmental Systems , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
N. Cao, X. Yan, Y. Shi, and C. Chen, “Ai-sketcher: A deep generative model for producing high-quality sketches,” in AAAI , 2019
2019
Later among the works it cites.
N. Zheng, Y. Jiang, and D. Huang, “Strokenet: A neural painting environment,” in ICLR , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
K. Li, K. Pang, Y.-Z. Song, T. Xiang, T. M. Hospedales, and H. Zhang, “Toward deep universal sketch perceptual grouper,” TIP , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
Y. Guo, Z. Zhang, C. Han, W. Hu, C. Li, and T.-T. Wong, “Deep line drawing vectorization via line subdivision and topology reconstruction,” in Computer Graphics Forum , 2019
2019
Later among the works it cites.
L. Donati, S. Cesano, and A. Prati, “A complete hand-drawn sketch vectorization framework,” Multimedia Tools and Applications , 2019
2019
Later among the works it cites.
J. Jiang, R. Wang, S. Lin, and F. Wang, “Sfsegnet: Parse freehand sketches using deep fully convolutional networks,” in IJCNN , 2019
2019
Later among the works it cites.
K. Mukherjee, R. X. Hawkins, and J. E. Fan, “Communicating semantic part information in drawings,” in Annual Conference of the Cognitive Science Society , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
X. Xu, M. Xie, P. Miao, W. Qu, W. Xiao, H. Zhang, X. Liu, and T.-T. Wong, “Perceptual-aware sketch simplification based on integrated vgg layers,” TVCG , 2019
2019
Later among the works it cites.
U. R. Muhammad, Y. Yang, T. M. Hospedales, T. Xiang, and Y.-Z. Song, “Goal-driven sequential data abstraction,” in ICCV , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
2019
Later among the works it cites.
Y. Wang, F. Huang, Y. Zhang, R. Feng, T. Zhang, and W. Fan, “Deep cascaded cross-modal correlation learning for fine-grained sketch-based image retrieval,” PR , 2019
2019
Later among the works it cites.
K. Pang, K. Li, Y. Yang, H. Zhang, T. M. Hospedales, T. Xiang, and Y.-Z. Song, “Generalising fine-grained sketch-based image retrieval,” in CVPR , 2019
2019
Later among the works it cites.
C. Li, Y. Zhou, and J. Yang, “Sketch-based image retrieval via a semi-heterogeneous cross-domain network,” in ICME Workshops , 2019
2019
Later among the works it cites.
J. Collomosse, T. Bui, and H. Jin, “Livesketch: Query perturbations for guided sketch-based visual search,” in CVPR , 2019
2019
Later among the works it cites.
H. Lin, Y. Fu, P. Lu, S. Gong, X. Xue, and Y.-G. Jiang, “Tc-net for isbir: Triplet classification network for instance-level sketch based image retrieval,” in MM , 2019
2019
Later among the works it cites.
J. Lei, Y. Song, B. Peng, Z. Ma, L. Shao, and Y.-Z. Song, “Semi-heterogeneous three-way joint embedding network for sketch-based image retrieval,” TCSVT , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
T. Dutta and S. Biswas, “Style-guided zero-shot sketch-based image retrieval,” in BMVC , 2019
2019
Later among the works it cites.
A. Dutta and Z. Akata, “Semantically tied paired cycle consistency for zero-shot sketch-based image retrieval,” in CVPR , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
A. Pandey, A. Mishra, V. Kumar Verma, and A. Mittal, “Adversarial joint-distribution learning for novel class sketch-based image retrieval,” in ICCV Workshops , 2019
2019
Later among the works it cites.
V. Kumar Verma, A. Mishra, A. Mishra, and P. Rai, “Generative model for zero-shot sketch-based image retrieval,” in CVPR Workshops , 2019
2019
Later among the works it cites.
Q. Liu, L. Xie, H. Wang, and A. L. Yuille, “Semantic-aware knowledge preservation for zero-shot sketch-based image retrieval,” in ICCV , 2019
2019
Later among the works it cites.
W. Wang, V. W. Zheng, H. Yu, and C. Miao, “A survey of zero-shot learning: Settings, methods, and applications,” TIST , 2019
2019
Later among the works it cites.
Y. Jo and J. Park, “Sc-fegan: Face editing generative adversarial network with user’s sketch and color,” in ICCV , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
A. Ghosh, R. Zhang, P. K. Dokania, O. Wang, A. A. Efros, P. H. S. Torr, and E. Shechtman, “Interactive sketch & fill: Multiclass sketch-to-image translation,” in ICCV , 2019
2019
Later among the works it cites.
M. Li, Z. Lin, R. Mech, E. Yumer, and D. Ramanan, “Photo-sketching: Inferring contour drawings from images,” in WACV , 2019
2019
Later among the works it cites.
Y. Zhang, G. Su, Y. Qi, and J. Yang, “Unpaired image-to-sketch translation network for sketch synthesis,” in VCIP , 2019
2019
Later among the works it cites.
C. Zou, H. Mo, C. Gao, R. Du, and H. Fu, “Language-based colorization of scene sketches,” TOG , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
2019
Later among the works it cites.
H. Chen, M. Valerio Giuffrida, P. Doerner, and S. A. Tsaftaris, “Adversarial large-scale root gap inpainting,” in CVPR Workshops , 2019
2019
Later among the works it cites.
J. Chen, J. Qin, L. Liu, F. Zhu, F. Shen, J. Xie, and L. Shao, “Deep sketch-shape hashing with segmented 3d stochastic viewing,” in CVPR , 2019
2019
Later among the works it cites.
S. Kuwabara, R. Ohbuchi, and T. Furuya, “Query by partially-drawn sketches for 3d shape retrieval,” in 2019 International Conference on Cyberworlds , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
M. Ye, S. Zhou, and H. Fu, “Deepshapesketch: Generating hand drawing sketches from 3d objects,” in IJCNN , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
M. Bessmeltsev and J. Solomon, “Vectorization of line drawings via polyvector fields,” TOG , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
2019
Later among the works it cites.
H. Kim, H. Y. Jhoo, E. Park, and S. Yoo, “Tag2pix: Line art colorization using text tag with secat and changing loss,” in ICCV , 2019
2019
Later among the works it cites.
C. Gao, Q. Liu, Q. Xu, L. Wang, J. Liu, and C. Zou, “Sketchycoco: Image generation from freehand scene sketches,” in CVPR , 2020
2020
Closest in time.
2020
Closest in time.
Q. Zheng, Z. Li, and A. Bargteil, “Learning to shadow hand-drawn sketches,” in CVPR , 2020
2020
Closest in time.
J. Lee, E. Kim, Y. Lee, D. Kim, J. Chang, and J. Choo, “Reference-based sketch image colorization using augmented-self reference and dense semantic correspondence,” in CVPR , 2020
2020
Closest in time.
S. Gui, Y. Zhu, X. Qin, and X. Ling, “Learning multi-level domain invariant features for sketch re-identification,” Neurocomputing , 2020
2020
Closest in time.
C. Yan, D. Vanderhaeghe, and Y. Gingold, “A benchmark for rough sketch cleanup,” TOG , 2020
2020
Closest in time.
M. Schrapel, F. Herzog, S. Ryll, and M. Rohs, “Watch my painting: The back of the hand as a drawing space for smartwatches,” CHI , 2020
2020
Closest in time.
M. Dvorožňák, D. Sýkora, C. Curtis, B. Curless, O. Sorkine-Hornung, and D. Salesin, “Monster Mash: A single-view approach to casual 3d modeling and animation,” ACM Transactions on Graphics , 2020
2020
Closest in time.
R. K. Sarvadevabhatla, S. Surya, T. Mittal, and V. B. Radhakrishnan, “Pictionary-style word-guessing on hand-drawn object sketches: dataset, analysis and deep network models,” TPAMI , 2020
2020
Closest in time.
A. Lamb, S. Ozair, V. Verma, and D. Ha, “Sketchtransfer: A new dataset for exploring detail-invariance and the abstractions learned by deep networks,” in WACV , 2020
2020
Closest in time.
F. Liu, C. Zou, X. Deng, R. Zuo, Y.-K. Lai, C. Ma, Y.-J. Liu, and H. Wang, “Scenesketcher: Fine-grained image retrieval with scene sketches,” in ECCV , 2020
2020
Closest in time.
X. Zhang, Y. Huang, Q. Zou, Y. Pei, R. Zhang, and S. Wang, “A hybrid convolutional neural network for sketch recognition,” PRL , 2020
2020
Closest in time.
G. Jain, S. Chopra, S. Chopra, and A. S. Parihar, “Transsketchnet: Attention-based sketch recognition using transformers,” in European Conference on Artificial Intelligence , 2020
2020
Closest in time.
J. Jiao, Y. Cao, M. Lau, and R. Lau, “Tactile sketch saliency,” in MM , 2020
2020
Closest in time.
Q. Jia, X. Fan, M. Yu, Y. Liu, D. Wang, and L. J. Latecki, “Coupling deep textural and shape features for sketch recognition,” in MM , 2020
2020
Closest in time.
2020
Closest in time.
2020
Closest in time.
C. Pan, J. Huang, J. Gong, and C. Chen, “Teach machine to learn: hand-drawn multi-symbol sketch recognition in one-shot,” Applied Intelligence , 2020
2020
Closest in time.
L. S. F. Ribeiro, T. Bui, J. Collomosse, and M. Ponti, “Sketchformer: Transformer-based representation for sketched structure,” in CVPR , 2020
2020
Closest in time.
H. Lin, Y. Fu, X. Xue, and Y.-G. Jiang, “Sketch-bert: Learning sketch bidirectional encoder representation from transformers by self-supervised learning of sketch gestalt,” in CVPR , 2020
2020
Closest in time.
J. Li, N. Gao, T. Shen, W. Zhang, T. Mei, and H. Ren, “Sketchman: Learning to create professional sketches,” in MM , 2020
2020
Closest in time.
A. Das, Y. Yang, T. Hospedales, T. Xiang, and Y.-Z. Song, “Béziersketch: A generative model for scalable vector sketches,” in ECCV , 2020
2020
Closest in time.
A. K. Bhunia, A. Das, U. R. Muhammad, Y. Yang, T. M. Hospedales, T. Xiang, Y. Gryaditskaya, and Y.-Z. Song, “Pixelor: A competitive sketching ai agent. so you think you can beat me?” ACM Transactions on Graphics , vol. 39, no. 6, 2020
2020
Closest in time.
2020
Closest in time.
2020
Closest in time.
T. Stanko, M. Bessmeltsev, D. Bommes, and A. Bousseau, “Integer-grid sketch simplification and vectorization,” in Computer Graphics Forum , 2020
2020
Closest in time.
U. Chaudhuri, B. Banerjee, A. Bhattacharya, and M. Datcu, “Crossatnet-a novel cross-attention based framework for sketch-based image retrieval,” Image and Vision Computing , 2020
2020
Closest in time.
F. Yang, Y. Wu, Z. Wang, X. Li, S. Sakti, and S. Nakamura, “Instance-level heterogeneous domain adaptation for limited-labeled sketch-to-photo retrieval,” TMM , 2020
2020
Closest in time.
T. Dutta and S. Biswas, “s-sbir: Style augmented sketch based image retrieval,” in WACV , 2020
2020
Closest in time.
A. K. Bhunia, Y. Yang, T. M. Hospedales, T. Xiang, and Y.-Z. Song, “Sketch less for more: On-the-fly fine-grained sketch based image retrieval,” in CVPR , 2020
2020
Closest in time.
K. Pang, Y. Yang, T. Hospedales, T. Xiang, and Y.-Z. Song, “Solving mixed-modal jigsaw puzzle for fine-grained sketch-based image retrieval,” in CVPR , 2020
2020
Closest in time.
A. Pandey, A. Mishra, V. K. Verma, A. Mittal, and H. Murthy, “Stacked adversarial network for zero-shot sketch based image retrieval,” in WACV , 2020
2020
Closest in time.
2020
Closest in time.
U. Chaudhuri, B. Banerjee, A. Bhattacharya, and M. Datcu, “A simplified framework for zero-shot cross-modal sketch data retrieval,” in CVPR Workshops , 2020
2020
Closest in time.
Z. Zhang, Y. Zhang, R. Feng, T. Zhang, and W. Fan, “Zero-shot sketch-based image retrieval via graph convolution network,” in AAAI , 2020
2020
Closest in time.
2020
Closest in time.
2020
Closest in time.
Z. Li, C. Deng, E. Yang, and D. Tao, “Staged sketch-to-image synthesis via semi-supervised generative adversarial networks,” TMM , 2020
2020
Closest in time.
2020
Closest in time.
M. Kampelmuhler and A. Pinz, “Synthesizing human-like sketches from natural images using a conditional convolutional decoder,” in WACV , 2020
2020
Closest in time.
S.-Y. Chen, W. Su, L. Gao, S. Xia, and H. Fu, “Deepfacedrawing: deep generation of face images from sketches,” TOG , 2020
2020
Closest in time.
2020
Closest in time.
2020
Closest in time.
F. Huang, E. Schoop, D. Ha, and J. Canny, “Scones: towards conversational authoring of sketches,” in International Conference on Intelligent User Interfaces , 2020
2020
Closest in time.
C. Hu, D. Li, Y. Yang, T. M. Hospedales, and Y.-Z. Song, “Sketch-a-segmenter: Sketch-based photo segmenter generation,” IEEE Transactions on Image Processing , vol. 29, pp. 9470–9481, 2020
2020
Closest in time.
2020
Closest in time.
P. Xu, C. K. Joshi, and X. Bresson, “Multigraph transformer for free-hand sketch recognition,” IEEE Transactions on Neural Networks and Learning Systems , 2021
2021
Closest in time.
L. Zhang, C. Li, E. Simo-Serra, Y. Ji, T.-T. Wong, and C. Liu, “User-Guided Line Art Flat Filling with Split Filling Mechanism,” in CVPR , 2021
2021
Closest in time.
M. Yuan and E. Simo-Serra, “Line Art Colorization with Concatenated Spatial Attention,” in CVPR Workshops , 2021
2021
Closest in time.
A. Das, Y. Yang, T. M. Hospedales, T. Xiang, and Y.-Z. Song, “Cloud2curve: Generation and vectorization of parametric sketches,” in CVPR , 2021
2021
Closest in time.
A. K. Bhunia, P. N. Chowdhury, Y. Yang, T. M. Hospedales, T. Xiang, and Y.-Z. Song, “Vectorization and rasterization: Self-supervised learning for sketch and handwriting,” in CVPR , 2021
2021
Closest in time.
S. Ge, V. Goswami, L. Zitnick, and D. Parikh, “Creative sketch generation,” in ICLR , 2021
2021
Closest in time.
A. D. Parakkat, M.-P. R. Cani, and K. Singh, “Color by numbers: Interactive structuring and vectorization of sketch imagery,” in CHI , 2021
2021
Closest in time.
A. Fuentes and J. M. Saavedra, “Sketch-qnet: A quadruplet convnet for color sketch-based image retrieval,” in CVPR Workshops , 2021
2021
Closest in time.
P. Torres and J. M. Saavedra, “Compact and effective representations for sketch-based image retrieval,” in CVPR Workshops , 2021
2021
Closest in time.
A. Qi, Y. Gryaditskaya, J. Song, Y. Yang, Y. Qi, T. M. Hospedales, T. Xiang, and Y.-Z. Song, “Toward fine-grained sketch-based 3d shape retrieval,” IEEE Transactions on Image Processing , vol. 30, pp. 8595–8606, 2021
2021
Closest in time.
S.-H. Zhang, Y.-C. Guo, and Q.-W. Gu, “Sketch2model: View-aware 3d modeling from single free-hand sketches,” in CVPR , 2021
2021
Closest in time.
K. D. Willis, P. K. Jayaraman, J. G. Lambourne, H. Chu, and Y. Pu, “Engineering sketch generation for computer-aided design,” in CVPR Workshops , 2021
2021
Closest in time.
H. Mo, E. Simo-Serra, C. Gao, C. Zou, and R. Wang, “General Virtual Sketching Framework for Vector Line Art,” TOG , 2021
2021
Closest in time.
R. B. Venkataramaiyer, A. Joshi, S. Narang, and V. P. Namboodiri, “Shad3s: A model to sketch, shade and shadow,” in WACV , 2021
2021
Closest in time.
K. T. Yesilbek and M. Sezgin, “On training sketch recognizers for new domains,” in CVPR Workshops , 2021
2021
Closest in time.