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SketchZooms: Deep multi-view descriptors for matching line drawings [article]

Pablo Navarro, José Ignacio Orlando, Claudio Delrieux, Emmanuel Iarussi
2021 arXiv   pre-print

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2019 pre-print arXiv:1912.05019v1 fatcat:z3o65wkl6vdhdju7umswsvstpe
This becomes particularly challenging for sketch images, due to the varying nature of human drawing style, projection distortions and viewport changes.  ...  To this end, we have specifically crafted a data set of synthetic sketches using non-photorealistic rendering over a large collection of part-based registered 3D models.  ...  We thank the NVIDIA Corporation for their GPU donation.  ... 
arXiv:1912.05019v2 fatcat:ct7se4t6ondtldpxe3mcakdcoq
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Pablo Navarro, José Ignacio Orlando, Claudio Delrieux, Emmanuel Iarussi. "SketchZooms: Deep multi-view descriptors for matching line drawings." arXiv (2021)

Smart Fashion: A Review of AI Applications in the Fashion Apparel Industry [article]

Seyed Omid Mohammadi, Ahmad Kalhor
2021 arXiv   pre-print

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2021 pre-print
arXiv:2111.00905v1 fatcat:6rws7p6vqbg35aq3eh6yaccqcm
The fashion industry is on the verge of an unprecedented change.  ...  For each task, a time chart is provided to analyze the progress through the years.  ...  Systems Recommender systems suggest fashion items based on similarity, style, color, user preference, and many more different schemes.  ... 
arXiv:2111.00905v2 fatcat:6n6d62lntjfu5pxmjzgi4mpv6i
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Seyed Omid Mohammadi, Ahmad Kalhor. "Smart Fashion: A Review of AI Applications in the Fashion Apparel Industry." arXiv (2021)

3D Sketching using Multi-View Deep Volumetric Prediction

Johanna Delanoy, Mathieu Aubry, Phillip Isola, Alexei A. Efros, Adrien Bousseau
2018 Proceedings of the ACM on Computer Graphics and Interactive Techniques  

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2018 accepted
arXiv:1707.08390v4 fatcat:3aludkpwsbclrotqsaqpi3ppq4
2018 pre-print
arXiv:1707.08390v3 fatcat:7aejw7g3pzea3kbj37slzfepn4
2017 pre-print
arXiv:1707.08390v2 fatcat:lnav6siorfhszoxtpoom3jlxvq
2017 pre-print
arXiv:1707.08390v1 fatcat:7r5bsjwnajbexcstll265jvrei
We propose a data-driven approach that tackles this challenge by learning to reconstruct 3D shapes from one or more drawings.  ...  Sketch-based modeling strives to bring the ease and immediacy of drawing to the 3D world.  ...  ACKNOWLEDGMENTS Many thanks to Yulia Gryaditskaya for sketching several of our results, and for her help on the renderings and video.  ... 
doi:10.1145/3203197 dblp:journals/pacmcgit/DelanoyAIEB18 fatcat:vwt4h6uo5rgejae42wo4s6nqga
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Johanna Delanoy, Mathieu Aubry, Phillip Isola, Alexei A. Efros, Adrien Bousseau. "3D Sketching using Multi-View Deep Volumetric Prediction." Proceedings of the ACM on Computer Graphics and Interactive Techniques 1.1 (2018) 1-22

DeepSketch2Face

Xiaoguang Han, Chang Gao, Yizhou Yu
2017 ACM Transactions on Graphics  

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2017 pre-print
arXiv:1706.02042v1 fatcat:dvtlej5uefgrzgpzdlxi5p6ph4
In this paper, we propose a deep learning based sketching system for 3D face and caricature modeling.  ...  A novel CNN based deep regression network is designed for inferring 3D face models from 2D sketches.  ...  ACKNOWLEDGMENTS The authors would like to thank the reviewers for their constructive comments, and the participants of our user study for their precious time.  ... 
doi:10.1145/3072959.3073629 fatcat:fa23253dmzhd5afvelnwcjjlqy
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Xiaoguang Han, Chang Gao, Yizhou Yu. "DeepSketch2Face." ACM Transactions on Graphics 36.4 (2017) 1-12

Deep Learning for Free-Hand Sketch: A Survey [article]

Peng Xu, Timothy M. Hospedales, Qiyue Yin, Yi-Zhe Song, Tao Xiang, Liang Wang
2022 arXiv   pre-print

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2020 pre-print
arXiv:2001.02600v1 fatcat:4csrjsnzk5fcfcahs5zadhancm
2020 pre-print
arXiv:2001.02600v2 fatcat:a2jb3u4hnzcy5abtimont3nod4
The main contents of this survey include: (i) A discussion of the intrinsic traits and unique challenges of free-hand sketch, to highlight the essential differences between sketch data and other data modalities  ...  (ii) A review of the developments of free-hand sketch research in the deep learning era, by surveying existing datasets, research topics, and the state-of-the-art methods through a detailed taxonomy and  ...  However, such sampling and meta-data are necessary for studying changes in drawing style with these covariates, as well as for ensuring that sketch-based applications work well for users of different backgrounds  ... 
arXiv:2001.02600v3 fatcat:lek5sivzsrat3i52lqh2eifnia
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Peng Xu, Timothy M. Hospedales, Qiyue Yin, Yi-Zhe Song, Tao Xiang, Liang Wang. "Deep Learning for Free-Hand Sketch: A Survey." arXiv (2022)

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, Ryutarou Ohbuchi, Pedro B. Pascoal (+1 others)
2014 Computer Vision and Image Understanding  

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Sketch-based 3D shape retrieval has become an important research topic in content-based 3D object retrieval.  ...  Six and five (nine in total) distinct sketch-based 3D shape retrieval methods have competed each other in these two contests, respectively.  ...  [5] provided us the largest sketch-based 3D shape retrieval benchmark until 2012, based on the Princeton Shape Benchmark (PSB) [6] with one user sketch for each PSB model.  ... 
doi:10.1016/j.cviu.2013.11.008 fatcat:3stzuphlo5ds5emnhtceepojcu
Citation

Bo Li, Yijuan Lu, Afzal Godil, Tobias Schreck, Benjamin Bustos, Alfredo Ferreira, Takahiko Furuya, Manuel J. Fonseca, Henry Johan, Takahiro Matsuda, Ryutarou Ohbuchi, Pedro B. Pascoal, Jose M. Saavedra. "A comparison of methods for sketch-based 3D shape retrieval." Computer Vision and Image Understanding (2014) 57-80

DrawingInStyles: Portrait Image Generation and Editing with Spatially Conditioned StyleGAN [article]

Wanchao Su, Hui Ye, Shu-Yu Chen, Lin Gao, Hongbo Fu
2022 arXiv   pre-print

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2022 pre-print
arXiv:2203.02762v1 fatcat:kuutyda5jbcyxdcdgnyr6iggu4
2022 pre-print
arXiv:2203.02762v2 fatcat:rdtqqesbuzcotii2h5cfbteoj4
Based on SC-StyleGAN, we present DrawingInStyles, a novel drawing interface for non-professional users to easily produce high-quality, photo-realistic face images with precise control, either from scratch  ...  The recently proposed StyleGAN architectures achieve state-of-the-art generation ability but the original StyleGAN is not friendly for sketch-based creation due to its unconditional generation nature.  ...  re-ranks the face sketches retrieved from the previous step, To disentangle the high-level style geometries from the low- based on their similarity (Section 4.2) to the user-drawn level style appearances  ... 
arXiv:2203.02762v3 fatcat:244tp46ws5gevbbii33xqh7q3i
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Wanchao Su, Hui Ye, Shu-Yu Chen, Lin Gao, Hongbo Fu. "DrawingInStyles: Portrait Image Generation and Editing with Spatially Conditioned StyleGAN." arXiv (2022)

Big Data driven Product Design: A Survey [article]

Huafeng Quan, Shaobo Li, Changchang Zeng, Hongjing Wei, Jianjun Hu
2021 arXiv   pre-print

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We believe that this study can draw increasing attention to modern data driven product design.  ...  This paper aims to conduct a comprehensive survey on big data driven product design.  ...  Traditional methods require designers to process drawing skills, such as hand drawing, or 3D modeling. The big data driven method provides simpler operations and does not require drawing skills.  ... 
arXiv:2109.11424v1 fatcat:ntw77c3grbbbllerzrwna32aem
Open Access
Citation

Huafeng Quan, Shaobo Li, Changchang Zeng, Hongjing Wei, Jianjun Hu. "Big Data driven Product Design: A Survey." arXiv (2021)

Deep Image Synthesis from Intuitive User Input: A Review and Perspectives [article]

Yuan Xue, Yuan-Chen Guo, Han Zhang, Tao Xu, Song-Hai Zhang, Xiaolei Huang
2021 arXiv   pre-print

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2021 pre-print
arXiv:2107.04240v1 fatcat:ahu54z6n3ncbja7xsejzleuhzq
In many applications of computer graphics, art and design, it is desirable for a user to provide intuitive non-image input, such as text, sketch, stroke, graph or layout, and have a computer system automatically  ...  networks (GANs), variational autoencoders (VAEs), and flow-based methods have enabled more powerful and versatile image generation tasks.  ...  As the user draws a sketch of a desired object type, the system automatically recommends completions and fills the shape with class-conditioned texture.  ... 
arXiv:2107.04240v2 fatcat:ticrsi27nzhozmw7dp7wwja2ni
Open Access Multiple Versions
Citation

Yuan Xue, Yuan-Chen Guo, Han Zhang, Tao Xu, Song-Hai Zhang, Xiaolei Huang. "Deep Image Synthesis from Intuitive User Input: A Review and Perspectives." arXiv (2021)

Computational Support for Sketching in Design: A Review

Gabe Johnson, Mark D. Gross, Jason Hong, Ellen Yi-Luen Do
2007 Foundations and Trends® in Human–Computer Interaction  

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Second, we survey computational support for sketching, including methods for performing sketch recognition and managing ambiguity, techniques for modeling recognizable elements, and humancomputer interaction  ...  techniques for working with sketches.  ...  Styling Based on Existing 3D Geometry In many 3D sketching systems, the visual representation is often beautified during reconstruction from 2D to 3D.  ... 
doi:10.1561/1100000013 fatcat:5r74v4r56nasdedplfnemebpw4
Citation

Gabe Johnson, Mark D. Gross, Jason Hong, Ellen Yi-Luen Do. "Computational Support for Sketching in Design: A Review." Foundations and Trends® in Human–Computer Interaction (2007) 1-93

Deep image synthesis from intuitive user input: A review and perspectives

Yuan Xue, Yuan-Chen Guo, Han Zhang, Tao Xu, Song-Hai Zhang, Xiaolei Huang
2021 Computational Visual Media  

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AbstractIn many applications of computer graphics, art, and design, it is desirable for a user to provide intuitive non-image input, such as text, sketch, stroke, graph, or layout, and have a computer  ...  networks (GANs), variational autoencoders (VAEs), and flow-based methods have enabled more powerful and versatile image generation approaches.  ...  National Natural Science Foundation of China (Project Nos. 61521002 and 61772298), a Research Grant of Beijing Higher Institution Engineering Research Center, and the Tsinghua-Tencent Joint Laboratory for  ... 
doi:10.1007/s41095-021-0234-8 fatcat:ot6dyrrrsnakxob4jzw4zld7zu
DOAJ
Citation

Yuan Xue, Yuan-Chen Guo, Han Zhang, Tao Xu, Song-Hai Zhang, Xiaolei Huang. "Deep image synthesis from intuitive user input: A review and perspectives." Computational Visual Media 8.1 (2021) 3-31

Modelling Of Visual Feature Derivation In The Vizir Framework

Horst Eidenberger
2004 Zenodo  

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ACKNOWLEDGEMENTS The author would like to thank Christian Breiteneder and Roman Divotkey for their valuable suggestions for improvement.  ...  paradigms for feature extraction, querying (e.g. 3D user interfaces for integrated browsing and retrieval) and evaluation.  ...  It communicates with query engines, user interfaces and media databases through XML messages (based on the Multimedia Retrieval Markup Language, MRML [5] ) and web services.  ... 
doi:10.5281/zenodo.38261 fatcat:zvzez7ogwngfbdqa2ccelfgxsu
Open Access
Citation

Horst Eidenberger. "Modelling Of Visual Feature Derivation In The Vizir Framework." Zenodo (2004)

ExquiMo: An Exquisite Corpse Tool for Collaborative 3D Shape Design

Warunika Ranaweera, Parmit Chilana, Daniel Cohen-Or, Hao Zhang
2017 Journal of Computer Science and Technology  

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We introduce a shape modeling tool, ExquiMo, which is guided by the idea of improving the creativity of 3D shape designs through collaboration.  ...  We demonstrate the effectiveness of collaborative modeling for both man-made and natural shapes.  ...  Their 3D modeling tool provides data-driven suggestions for suitable shape parts to the users so as to "stimulate" their creativity.  ... 
doi:10.1007/s11390-017-1789-9 fatcat:5ln6f3dms5efpi2ihjs5ysrcgy
Citation

Warunika Ranaweera, Parmit Chilana, Daniel Cohen-Or, Hao Zhang. "ExquiMo: An Exquisite Corpse Tool for Collaborative 3D Shape Design." Journal of Computer Science and Technology 32.6 (2017) 1138-1149

Interactive Sketch Fill: Multiclass Sketch-to-Image Translation [article]

Arnab Ghosh and Richard Zhang and Puneet K. Dokania and Oliver Wang and Alexei A. Efros and Philip H.S. Torr and Eli Shechtman
2019 arXiv   pre-print

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2019 pre-print
arXiv:1909.11081v1 fatcat:vfnt2olmk5bhlbk2bks4mdzydq
This enables a feedback loop, where the user can edit their sketch based on the network's recommendations, visualizing both the completed shape and final rendered image while they draw.  ...  We propose an interactive GAN-based sketch-to-image translation method that helps novice users create images of simple objects.  ...  We propose a new GAN-based interactive image generation system for drawing objects from scratch that: 1) generates full images given partial user strokes (or sketches); 2) serves as a recommender system  ... 
arXiv:1909.11081v2 fatcat:yxljx4ujqrepxg5uufevynh63e
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Citation

Arnab Ghosh and Richard Zhang and Puneet K. Dokania and Oliver Wang and Alexei A. Efros and Philip H.S. Torr and Eli Shechtman. "Interactive Sketch Fill: Multiclass Sketch-to-Image Translation." arXiv (2019)

A Natural and Immersive Virtual Interface for the Surgical Safety Checklist Training

Andrea Ferracani, Daniele Pezzatini, Alberto Del Bimbo
2014 Proceedings of the 2014 ACM International Workshop on Serious Games - SeriousGames '14  

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With the focus on natural language and entity understanding, for instance, we have improved Bing's ability to understand the user intent beyond queries and keywords.  ...  By leveraging big data from billions of search queries, billions of images on the web and from the social networks, and billions of user clicks, we have designed massive machine learning systems to continuously  ...  Distributed Virtual Environments Interactive 3D Animation Creation and Viewing System Based on Motion Graph and a Pose Estimation Method Color Transfer Based on Spatial Structure for Telepresence  ... 
doi:10.1145/2656719.2656725 dblp:conf/mm/FerracaniPB14a fatcat:obsb2i4iybhu3dq77hujvjtbze
Citation

Andrea Ferracani, Daniele Pezzatini, Alberto Del Bimbo. "A Natural and Immersive Virtual Interface for the Surgical Safety Checklist Training." Proceedings of the 2014 ACM International Workshop on Serious Games - SeriousGames '14 (2014) 27-32

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