11.2.1.3.7 Artistic Recognition, Interpretation

Chapter Contents (Back)
Aesthetic Quality. Artitstic Interpretation.
See also Graphics, Rendering Issues Related to Artistic Interpretation.

Jiang, S.Q.[Shu-Qiang], Huang, Q.M.[Qing-Ming], Ye, Q.X.[Qi-Xiang], Gao, W.[Wen],
An effective method to detect and categorize digitized traditional Chinese paintings,
PRL(27), No. 7, May 2006, pp. 734-746.
Elsevier DOI 0604
Traditional Chinese painting; Image classification; Edge-size histogram BibRef

Taylor, R.P., Guzman, R., Martin, T.P., Hall, G.D.R., Micolich, A.P., Jonas, D., Scannell, B.C., Fairbanks, M.S., Marlow, C.A.,
Authenticating Pollock paintings using fractal geometry,
PRL(28), No. 6, 15 April 2007, pp. 695-702.
Elsevier DOI 0703
Abstract art; Jackson Pollock; Authenticity; Fractals BibRef

Postma, E.O.[Eric O.], van den Herik, H.J.[H. Jaap], van der Lubbe, J.[Jan],
Paintings and writings in the hands of scientists,
PRL(28), No. 6, 15 April 2007, pp. 671-672.
Elsevier DOI 0703
BibRef

Shen, J.L.[Jia-Lie],
Stochastic modeling western paintings for effective classification,
PR(42), No. 2, February 2009, pp. 293-301.
Elsevier DOI 0810
Classic western paintings; Identification; Image retrieval; Cultural heritage BibRef

Lee, J.W.[Joon-Whoan], Park, E.J.[Eun-Jong],
Fuzzy Similarity-Based Emotional Classification of Color Images,
MultMed(13), No. 5, 2011, pp. 1031-1039.
IEEE DOI 1110
evaluating an emotional response to color images. BibRef

Arabadjis, D., Rousopoulos, P., Papaodysseus, C., Exarhos, M., Panagopoulos, M., Papazoglou-Manioudaki, L.,
Optimization in Differentiable Manifolds in Order to Determine the Method of Construction of Prehistoric Wall Paintings,
PAMI(33), No. 11, November 2011, pp. 2229-2244.
IEEE DOI 1110
Fit parametric curves to prehistoric wall painting. BibRef

Libeks, J.[Janis], Turnbull, D.[Douglas],
You Can Judge an Artist by an Album Cover: Using Images for Music Annotation,
MultMedMag(18), No. 4, October-December 2011, pp. 30-37.
IEEE DOI 1112
BibRef

Xu, S.H.[Song-Hua], Jiang, H.[Hao], Lau, F.C.M.[Francis C.M.], Pan, Y.H.[Yun-He],
Computationally Evaluating and Reproducing the Beauty of Chinese Calligraphy,
IEEE_Int_Sys(27), No. 3, May-June 2012, pp. 63-72.
IEEE DOI 1208
BibRef

Hughes, J.M.[James M.], Mao, D.[Dong], Rockmore, D.N.[Daniel N.], Wang, Y.[Yang], Wu, Q.A.[Qi-Ang],
Empirical Mode Decomposition Analysis for Visual Stylometry,
PAMI(34), No. 11, November 2012, pp. 2147-2157.
IEEE DOI 1209
Measurement and comparisons of individual style in the visual arts. BibRef

Rosin, P.[Paul], Collomosse, J.P.[John P.], (Eds.)
Image and Video-based Artistic Stylisation,
Springer2013. ISBN 978-1-4471-4518-9 Buy this book: Image and Video-based Artistic Stylisation (Computational Imaging and Vision)
WWW Link. 1211
Non-photorealistic rendering BibRef

Lin, L., Zeng, K., Wang, Y., Xu, Y.Q., Zhu, S.C.,
Video Stylization: Painterly Rendering and Optimization With Content Extraction,
CirSysVideo(23), No. 4, April 2013, pp. 577-590.
IEEE DOI 1304
BibRef

Xie, N.[Ning], Hachiya, H.[Hirotaka], Sugiyama, M.[Masashi],
Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting,
IEICE(E96-D), No. 5, May 2013, pp. 1134-1144.
WWW Link. 1305
BibRef

Carneiro, G.,
Artistic Image Analysis Using Graph-Based Learning Approaches,
IP(22), No. 8, 2013, pp. 3168-3178.
IEEE DOI artistic image analysis; Content-based image retrieval 1307
BibRef

Sheng, J.C.[Jia-Chuan], Jiang, J.M.[Jian-Min],
Recognition of Chinese artists via windowed and entropy balanced fusion in classification of their authored ink and wash paintings (IWPs),
PR(47), No. 2, 2014, pp. 612-622.
Elsevier DOI 1311
Analysis of ink wash paintings BibRef

Cooper, B.[Bonnie], Lee, B.B.[Barry B.],
Independence and interaction of luminance and chromatic contributions to spatial hyperacuity performance,
JOSA-A(31), No. 4, April 2014, pp. A394-A400.
DOI Link 1404
Color vision; Psychophysics; Spatial discrimination BibRef

Devinck, F.[Frederic], Gerardin, P.[Peggy], Dojat, M.[Michel], Knoblauch, K.[Kenneth],
Spatial selectivity of the watercolor effect,
JOSA-A(31), No. 4, April 2014, pp. A1-A6.
DOI Link 1404
Vision, color, and visual optics BibRef

Monroy Kuhn, J.A.[Juan Antonio], Bell, P.[Peter], Ommer, B.[Björn],
Morphological analysis for investigating artistic images,
IVC(32), No. 6-7, 2014, pp. 414-423.
Elsevier DOI 1406
BibRef
Earlier:
Shaping Art with Art: Morphological Analysis for Investigating Artistic Reproductions,
VISART12(I: 571-580).
Springer DOI 1210
Shape analysis BibRef

John Asmus: Optical techniques and the mysterious Mona Lisa,
SPIE(Newsroom), April 15, 2014
DOI Link 1407
A video interview. A lifetime in lasers began with one of Maiman's originals at Caltech, and has led this art-restoration pioneer to analyze and restore some of the world's most famous artworks. BibRef

Khan, F.S.[Fahad Shahbaz], Beigpour, S.[Shida], van de Weijer, J.[Joost], Felsberg, M.[Michael],
Painting-91: a large scale database for computational painting categorization,
MVA(25), No. 6, 2014, pp. 1385-1397.
Springer DOI 1408
BibRef

Jacobsen, C.R.[C. Robert], Nielsen, M.[Morten],
Investigation of the Effects of Data Collection on Visual Stylometry,
IJIG(14), No. 04, 2014, pp. 1450019.
DOI Link 1412
analysing visual art by mathematical and statistical methods BibRef

Condorovici, R.G.[Razvan George], Florea, C.[Corneliu], Vertan, C.[Constantin],
Automatically classifying paintings with perceptual inspired descriptors,
JVCIR(26), No. 1, 2015, pp. 222-230.
Elsevier DOI 1502
BibRef
And: Erratum: JVCIR(29), No. 1, 2015, pp. 153-.
Elsevier DOI 1504
Painting BibRef

Abry, P., Roux, S., Wendt, H., Messier, P., Klein, A., Tremblay, N., Borgnat, P., Jaffard, S., Vedel, B., Coddington, J., Daffner, L.,
Multiscale Anisotropic Texture Analysis and Classification of Photographic Prints: Art scholarship meets image processing algorithms,
SPMag(32), No. 4, July 2015, pp. 18-27.
IEEE DOI 1506
Anisotropic magnetoresistance BibRef

Johnson, C., Sethares, W., Ellis, M., Haqqi, S.,
Hunting for Paper Moldmates Among Rembrandt's Prints: Chain-line pattern matching,
SPMag(32), No. 4, July 2015, pp. 28-37.
IEEE DOI 1506
Art BibRef

van Noord, N., Hendriks, E., Postma, E.,
Toward Discovery of the Artist's Style: Learning to recognize artists by their artworks,
SPMag(32), No. 4, July 2015, pp. 46-54.
IEEE DOI 1506
Adaptive filters BibRef

Ghaderi, M.[Mohammad], Ruiz, F.[Francisco], Agell, N.[Núria],
Understanding the impact of brand colour on brand image: A preference disaggregation approach,
PRL(67, Part 1), No. 1, 2015, pp. 11-18.
Elsevier DOI 1511
Preference disaggregation BibRef

Gbèhounou, S.[Syntyche], Lecellier, F.[François], Fernandez-Maloigne, C.[Christine],
Evaluation of local and global descriptors for emotional impact recognition,
JVCIR(38), No. 1, 2016, pp. 276-283.
Elsevier DOI 1605
Images BibRef

Xu, P.F.[Peng-Fei], Zheng, X.[Xia], Chang, X.J.[Xiao-Jun], Miao, Q.G.[Qi-Guang], Tang, Z.Y.[Zhan-Yong], Chen, X.J.[Xiao-Jiang], Fang, D.Y.[Ding-Yi],
Artistic information extraction from Chinese calligraphy works via Shear-Guided filter,
JVCIR(40, Part B), No. 1, 2016, pp. 791-807.
Elsevier DOI 1610
Artistic information extraction BibRef

Sun, T.C.[Tian-Cheng], Wang, Y.L.[Yu-Long], Yang, J.[Jian], Hu, X.L.[Xiao-Lin],
Convolution Neural Networks With Two Pathways for Image Style Recognition,
IP(26), No. 9, September 2017, pp. 4102-4113.
IEEE DOI 1708
feature extraction, image classification, image retrieval, image texture, neural nets, AlexNet CNN, ImageNet classification data set, VGG-19 CNN, artwork analysis, BibRef

Nanni, L.[Loris], Ghidoni, S.[Stefano],
How could a subcellular image, or a painting by Van Gogh, be similar to a great white shark or to a pizza?,
PRL(85), No. 1, 2017, pp. 1-7.
Elsevier DOI 1612
Deep convolutional neural networks BibRef

Puthenputhussery, A.[Ajit], Liu, Q.F.[Qing-Feng], Liu, C.J.[Cheng-Jun],
A Sparse Representation Model Using the Complete Marginal Fisher Analysis Framework and Its Applications to Visual Recognition,
MultMed(19), No. 8, August 2017, pp. 1757-1770.
IEEE DOI 1708
BibRef
Earlier:
Sparse Representation Based Complete Kernel Marginal Fisher Analysis Framework for Computational Art Painting Categorization,
ECCV16(VIII: 612-627).
Springer DOI 1611
Dictionaries, Encoding, Feature extraction, Null space, Optimization, Sparse matrices, Visualization, Discriminative sparse representation, column space, complete marginal Fisher analysis (CMFA), BibRef

Puthenputhussery, A.[Ajit], Liu, Q.F.[Qing-Feng], Liu, H., Liu, C.J.[Cheng-Jun],
Generative and Discriminative Sparse Coding for Image Classification Applications,
WACV18(1824-1832)
IEEE DOI 1806
feature extraction, image classification, image coding, image representation, learning (artificial intelligence), Training BibRef

Chu, W., Wu, Y.,
Image Style Classification Based on Learnt Deep Correlation Features,
MultMed(20), No. 9, September 2018, pp. 2491-2502.
IEEE DOI 1809
art, convolution, correlation methods, feature extraction, feedforward neural nets, image classification, image texture, learnt correlation features BibRef

Jiang, S.H.[Shu-Hui], Shao, M.[Ming], Jia, C.C.[Cheng-Cheng], Fu, Y.[Yun],
Learning Consensus Representation for Weak Style Classification,
PAMI(40), No. 12, December 2018, pp. 2906-2919.
IEEE DOI 1811
Visualization, Feature extraction, Data visualization, Principal component analysis, Encoding, Deep learning, auto-encoder BibRef

Florea, C.[Corneliu], Gieseke, F.[Fabian],
Artistic movement recognition by consensus of boosted SVM based experts,
JVCIR(56), 2018, pp. 220-233.
Elsevier DOI 1811
Randomized boosted SVMs, Multi-scale topography, Painting style recognition, Consensus of experts, Ensembles BibRef

Yang, H.[Heekyung], Min, K.[Kyungha],
Classification of basic artistic media based on a deep convolutional approach,
VC(36), No. 3, March 2020, pp. 559-578.
WWW Link. 2002
BibRef

Garcia, N.[Noa], Renoust, B.[Benjamin], Nakashima, Y.[Yuta],
ContextNet: representation and exploration for painting classification and retrieval in context,
MultInfoRetr(9), No. 1, March 2020, pp. 17-30.
WWW Link. 2003
BibRef

Silva, J.M.[Jorge Miguel], Pratas, D.[Diogo], Antunes, R.[Rui], Matos, S.[Sérgio], Pinho, A.J.[Armando J.],
Automatic analysis of artistic paintings using information-based measures,
PR(114), 2021, pp. 107864.
Elsevier DOI 2103
Image analysis, Data compression, BDM, Artistic paintings, Algorithmic information theory BibRef

Ou, Y.J.[Yang-Jun], Chen, Z.Z.[Zhen-Zhong], Wu, F.[Feng],
Multimodal Local-Global Attention Network for Affective Video Content Analysis,
CirSysVideo(31), No. 5, 2021, pp. 1901-1914.
IEEE DOI 2105
Predicting emotional responses of movie audiences. BibRef

Guo, W.[Wenya], Zhang, Y.[Ying], Cai, X.[Xiangrui], Meng, L.[Lei], Yang, J.F.[Ju-Feng], Yuan, X.J.[Xiao-Jie],
LD-MAN: Layout-Driven Multimodal Attention Network for Online News Sentiment Recognition,
MultMed(23), 2021, pp. 1785-1798.
IEEE DOI 2106
Sentiment analysis, Visualization, Layout, Feature extraction, Analytical models, Neural networks, Image recognition, article layout BibRef

Wu, C.L.[Chun-Lei], Wang, J.N.[Jiang-Nan], Yuan, S.Z.[Shao-Zu], Wang, L.Q.[Lei-Quan], Zhang, W.S.[Wei-Shan],
Generate classical Chinese poems with theme-style from images,
PRL(149), 2021, pp. 75-82.
Elsevier DOI 2108
Image, Quatrain, Automatic generation, Theme, Style BibRef

Pfister, J.[Jan], Kobs, K.[Konstantin], Hotho, A.[Andreas],
Self-Supervised Multi-Task Pretraining Improves Image Aesthetic Assessment,
NTIRE21(816-825)
IEEE DOI 2109
Computational modeling, Neural networks, Training data, Distortion, Data models BibRef

Frank, S.J.[Steven J.],
State of the Art: This Convolutional Neural Network can Tell you Whether a Painting is a Fake,
Spectrum(58), No. 9, September 2021, pp. 26-31.
IEEE DOI 2109
Painting BibRef


Agrawal, R.[Rishabh], Sivaprasad, S.[Sarath], Pedanekar, N.[Niranjan],
Color Me Good: Branding in the Coloring Style of Movie Posters,
CVFAD21(3894-3898)
IEEE DOI 2109
Image segmentation, Visualization, Image color analysis, Semantics, Brightness BibRef

Conde, M.V.[Marcos V.], Turgutlu, K.[Kerem],
CLIP-Art: Contrastive Pre-training for Fine-Grained Art Classification,
CVFAD21(3951-3955)
IEEE DOI 2109
Training, Art, Image recognition, Databases, Natural languages, Neural networks BibRef

Santana, P.S.[Priscila Sánchez], Roman-Rangel, E.[Edgar],
Quantifying Visual Similarity for Artistic Styles,
MCPR21(187-197).
Springer DOI 2108
BibRef

Zhang, L.[Lili],
Research on Chinese Traditional Garden Immersive Aesthetic Experience in the Era of Artificial Intelligence,
DHM21(II:415-427).
Springer DOI 2108
BibRef

Lanitis, A., Theodosiou, Z., Partaourides, H.,
Artwork Identification in a Museum Environment: A Quantitative Evaluation of Factors Affecting Identification Accuracy,
EuroMed20(588-595).
Springer DOI 2106
BibRef

Karimi, A.[Akbar], Rossi, L.[Leonardo], Prati, A.[Andrea],
Adversarial Training for Aspect-Based Sentiment Analysis with BERT,
ICPR21(8797-8803)
IEEE DOI 2105
Training, Sentiment analysis, Bit error rate, Neural networks, Task analysis, Software development management BibRef

Thao, H.T.P.[Ha Thi Phuong], Balamurali, B.T., Herremans, D.[Dorien], Roig, G.[Gemma],
AttendAffectNet: Self-Attention based Networks for Predicting Affective Responses from Movies,
ICPR21(8719-8726)
IEEE DOI 2105
Training, Annotations, Neural networks, Streaming media, Predictive models, Motion pictures, Feature extraction BibRef

Fahn, C.S.[Chin-Shyurng], Wu, M.L.[Meng-Luen], Tsau, S.K.[Sheng-Kuei],
An Intelligent Photographing Guidance System Based on Compositional Deep Features and Intepretable Machine Learning Model,
ICPR21(7723-7729)
IEEE DOI 2105
Photography, Computational modeling, Machine learning, Predictive models, Feature extraction, Cameras, preference prediction BibRef

Castellano, G.[Giovanna], Vessio, G.[Gennaro],
Deep Convolutional Embedding for Digitized Painting Clustering,
ICPR21(2708-2715)
IEEE DOI 2105
Measurement, Visualization, Semantics, Metadata, Feature extraction, Knowledge discovery, Pattern recognition BibRef

Dai, Y.[Ying],
CNN-based repetitive self-revised learning for photos' aesthetics imbalanced classification,
ICPR21(331-338)
IEEE DOI 2105
Training data, Pattern recognition, photo aesthetic assessment, repetitive self-revised deep learning, dropping out sample, highlight BibRef

Castellano, G.[Giovanna], Vessio, G.[Gennaro],
A Brief Overview of Deep Learning Approaches to Pattern Extraction and Recognition in Paintings and Drawings,
FAPER20(487-501).
Springer DOI 2103
BibRef

Jain, N.[Nitisha], Bartz, C.[Christian], Bredow, T.[Tobias], Metzenthin, E.[Emanuel], Otholt, J.[Jona], Krestel, R.[Ralf],
Semantic Analysis of Cultural Heritage Data: Aligning Paintings and Descriptions in Art-historic Collections,
FAPER20(517-530).
Springer DOI 2103
BibRef

Lin, H.[Hubert], Van Zuijlen, M.[Mitchell], Wijntjes, M.W.A.[Maarten W. A.], Pont, S.C.[Sylvia C.], Bala, K.[Kavita],
Insights from a Large-scale Database of Material Depictions in Paintings,
FAPER20(531-545).
Springer DOI 2103
BibRef

Gonthier, N.[Nicolas], Gousseau, Y.[Yann], Ladjal, S.[Saïd],
An Analysis of the Transfer Learning of Convolutional Neural Networks for Artistic Images,
FAPER20(546-561).
Springer DOI 2103
BibRef

Roychowdhury, S.[Shounak],
Color Space Exploration of Paintings Using a Novel Probabilistic Divergence,
FAPER20(577-588).
Springer DOI 2103
BibRef

Aslan, S.[Sinem], Steels, L.[Luc],
Identifying Centres of Interest in Paintings Using Alignment and Edge Detection,
FAPER20(589-603).
Springer DOI 2103
BibRef

Teruggi, S.[Simone], Fassi, F.[Francesco],
Machines Learning for Mixed Reality,
FAPER20(613-627).
Springer DOI 2103
BibRef

Barra, P.[Paola], Barra, S.[Silvio], Narducci, F.[Fabio],
From Fully Supervised to Blind Digital Anastylosis on Dafne Dataset,
FAPER20(628-642).
Springer DOI 2103
BibRef

Olague, G.[Gustavo], Ibarra-Vázquez, G.[Gerardo], Chan-Ley, M.[Mariana], Puente, C.[Cesar], Soubervielle-Montalvo, C.[Carlos], Martinez, A.[Axel],
A Deep Genetic Programming Based Methodology for Art Media Classification Robust to Adversarial Perturbations,
ISVC20(I:68-79).
Springer DOI 2103
BibRef

Sindel, A., Maier, A., Christlein, V.,
Art2Contour: Salient Contour Detection in Artworks Using Generative Adversarial Networks,
ICIP20(788-792)
IEEE DOI 2011
Task analysis, Generative adversarial networks, Painting, Image edge detection, Generators, Training, Artworks BibRef

Cormier, M., Park, S., Beck, L.,
Automatic Classification of Woodcuts and Copperplate Engravings,
CRV20(85-92)
IEEE DOI 2006
Classification, art, illustrations BibRef

Fu, C.P.[Cheng-Peng], Wang, J.Q.[Jin-Qiang], Sang, J.[Jitao], Yu, J.[Jian], Xu, C.S.[Chang-Sheng],
Beyond Literal Visual Modeling: Understanding Image Metaphor Based on Literal-implied Concept Mapping,
MMMod20(I:111-123).
Springer DOI 2003
BibRef

Kim, J., Jun, J.Y., Hong, M., Shim, H., Ahn, J.,
Classification of Oil Painting Using Machine Learning With Visualized Depth Information,
CIPA19(617-623).
DOI Link 1912
BibRef

Wei, H., Gao, G.,
A Holistic Recognition Approach for Woodblock-Print Mongolian Words Based on Convolutional Neural Network,
ICIP19(2726-2730)
IEEE DOI 1910
Convolutional neural network, woodblock-print, classical Mongolian, imbalance distribution of samples, synthetic samples BibRef

Goeting, M.[Marijke],
Seeing the World Through Machinic Eyes: Reflections on Computer Vision in the Arts,
CVAA18(II:653-670).
Springer DOI 1905
BibRef

Lang, S.[Sabine], Ommer, B.[Björn],
Reflecting on How Artworks Are Processed and Analyzed by Computer Vision,
CVAA18(II:647-652).
Springer DOI 1905
BibRef

Sabatelli, M.[Matthia], Kestemont, M.[Mike], Daelemans, W.[Walter], Geurts, P.[Pierre],
Deep Transfer Learning for Art Classification Problems,
CVAA18(II:631-646).
Springer DOI 1905
BibRef

Jangtjik, K.A., Ho, T.T., Yeh, M.C., Hua, K.L.,
A CNN-LSTM framework for authorship classification of paintings,
ICIP17(2866-2870)
IEEE DOI 1803
Adaptation models, Correlation, Logic gates, Painting, Recurrent neural networks, Task analysis, Training, multiscale pyramid representation BibRef

van Noord, N., Postma, E.,
A Learned Representation of Artist-Specific Colourisation,
eHeritage17(2907-2915)
IEEE DOI 1802
Art, Decoding, Image color analysis, Painting, Training, Visualization BibRef

Bianco, S.[Simone], Mazzini, D.[Davide], Schettini, R.[Raimondo],
Deep Multibranch Neural Network for Painting Categorization,
CIAP17(I:414-423).
Springer DOI 1711
BibRef

Florea, C., Toca, C., Gieseke, F.,
Artistic Movement Recognition by Boosted Fusion of Color Structure and Topographic Description,
WACV17(569-577)
IEEE DOI 1609
Art, Databases, Image color analysis, Kernel, Painting, Support vector machines, Training BibRef

Florea, C.[Corneliu], Badea, M.[Mihai], Florea, L.[Laura], Vertan, C.[Constantin],
Domain Transfer for Delving into Deep Networks Capacity to De-Abstract Art,
SCIA17(I: 337-349).
Springer DOI 1706
BibRef

Vitorino, T.[Tatiana], Casini, A.[Andrea], Cucci, C.[Costanza], Picollo, M.[Marcello], Stefani, L.[Lorenzo],
When It Is Not Only About Color: The Importance of Hyperspectral Imaging Applied to the Investigation of Paintings,
CCIW17(175-183).
Springer DOI 1704
BibRef

Bianco, S.[Simone], Cusano, C.[Claudio], Schettini, R.[Raimondo],
Artistic Photo Filtering Recognition Using CNNs,
CCIW17(249-258).
Springer DOI 1704
BibRef

Seguin, B.[Benoit], Striolo, C.[Carlotta], di Lenardo, I.[Isabella], Kaplan, F.[Frederic],
Visual Link Retrieval in a Database of Paintings,
CVAA16(I: 753-767).
Springer DOI 1611
retrieve common visual patterns shared by series of paintings. BibRef

Folego, G., Gomes, O., Rocha, A.,
From impressionism to expressionism: Automatically identifying van Gogh's paintings,
ICIP16(141-145)
IEEE DOI 1610
Art BibRef

Kim, N.[Namil], Choi, Y.[Yukyung], Hwang, S.[Soonmin], Kweon, I.S.[In So],
Artrieval: Painting retrieval without expert knowledge,
ICIP15(1339-1343)
IEEE DOI 1512
color clustering BibRef

Fried, O.[Ohad], Shechtman, E.[Eli], Goldman, D.B.[Dan B.], Finkelstein, A.[Adam],
Finding distractors in images,
CVPR15(1703-1712)
IEEE DOI 1510
regions of an image that draw attention away from the main subjects. Remove them with inpainting. BibRef

Gao, Z.[Zhi], Shan, M.[Mo], Cheong, L.F.[Loong-Fah], Li, Q.Q.[Qing-Quan],
Adaptive Sparse Coding for Painting Style Analysis,
ACCV14(II: 102-117).
Springer DOI 1504
BibRef

Bar, Y.[Yaniv], Levy, N.[Noga], Wolf, L.[Lior],
Classification of Artistic Styles Using Binarized Features Derived from a Deep Neural Network,
VISART14(71-84).
Springer DOI 1504
BibRef

Chen, Q.[Qian], Carneiro, G.[Gustavo],
Artistic Image Analysis Using the Composition of Human Figures,
VISART14(117-132).
Springer DOI 1504
BibRef

Agarwal, S.[Siddharth], Karnick, H.[Harish], Pant, N.[Nirmal], Patel, U.[Urvesh],
Genre and Style Based Painting Classification,
WACV15(588-594)
IEEE DOI 1503
Accuracy BibRef

Blažek, J.[Jan], Soukup, J.[Jindrich], Zitová, B.[Barbara], Flusser, J.[Jan], Hradilová, J.[Janka], Hradil, D.[David], Tichý, T.[Tomáš],
M3art: A Database of Models of Canvas Paintings,
EuroMed14(176-185).
Springer DOI 1412
BibRef

Solina, F.[Franc], Majcen, G.[Gregor], Bovcon, N.[Narvika], Batagelj, B.[Borut],
Preservation of a Computer-Based Art Installation,
EuroMed14(643-650).
Springer DOI 1412
BibRef

Falvo, P.G.[Perla Gianni],
The Madonna of the Goldfinch by Raphael: Chamera of Perception,
EuroMed14(706-715).
Springer DOI 1412
BibRef

Stout, S.[Samantha], Cosentino, A.[Antonino], Scandurra, C.[Carmelo],
Non-invasive Materials Analysis Using Portable X-ray Fluorescence (XRF) in the Examination of Two Mural Paintings in the Catacombs of San Giovanni, Syracuse,
EuroMed14(697-705).
Springer DOI 1412
BibRef

Xiong, B.[Bo], Grauman, K.[Kristen],
Detecting Snap Points in Egocentric Video with a Web Photo Prior,
ECCV14(V: 282-298).
Springer DOI 1408
Those points that look like composed photos. BibRef

Ghorai, M., Chanda, B.,
A robust faint line detection and enhancement algorithm for mural images,
NCVPRIPG13(1-4)
IEEE DOI 1408
art BibRef

Deborah, H.[Hilda], George, S.[Sony], Hardeberg, J.Y.[Jon Yngve],
Pigment Mapping of the Scream (1893) Based on Hyperspectral Imaging,
ICISP14(247-256).
Springer DOI 1406
BibRef

Baltazar, A.[Aurélie], Baltazar, P.[Pascal], Frisson, C.[Christian],
An Interactive Device for Exploring Thematically Sorted Artworks,
MMMod14(II: 34-43).
Springer DOI 1405
BibRef

Liu, D.W.[Dong-Wei], Klette, R.[Reinhard],
Inverse Skeletal Strokes,
PSIVTWS13(1-11).
Springer DOI 1402
BibRef

Wu, T.[Tong], Polatkan, G.[Gungor], Steel, D.[David], Brown, W.[William], Daubechies, I.[Ingrid], Calderbank, R.[Robert],
Painting analysis using wavelets and probabilistic topic models,
ICIP13(3264-3268)
IEEE DOI 1402
Hidden Markov Trees BibRef

Guo, X.Y.[Xiao-Ying], Kurita, T.[Takio], Asano, C.M.[Chie Muraki], Asano, A.[Akira],
Visual complexity assessment of painting images,
ICIP13(388-392)
IEEE DOI 1402
Accuracy BibRef

Condorovici, R.G.[Razvan George], Florea, C.[Corneliu], Vertan, C.[Constantin],
Painting Scene Recognition Using Homogenous Shapes,
ACIVS13(262-273).
Springer DOI 1311
BibRef

Condorovici, R.G.[Razvan George], Florea, C.[Corneliu], Vrânceanu, R.[Ruxandra], Vertan, C.[Constantin],
Perceptually-Inspired Artistic Genre Identification System in Digitized Painting Collections,
SCIA13(687-696).
Springer DOI 1311
BibRef

Abe, K.[Kanako], Saleh, B.[Babak], Elgammal, A.[Ahmed],
An Early Framework for Determining Artistic Influence,
MM4CH13(198-207).
Springer DOI 1309
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Zhang, M.[Min], Atkinson, S.[Sarah], Alechina, N.[Natasha], Qiu, G.P.[Guo-Ping],
'A Is for Art': My Drawings, Your Paintings,
MM4CH13(308-317).
Springer DOI 1309
BibRef

Mallik, A.[Anupama], Chaudhury, S.[Santanu], Madan, S.[Shipra], Dinesh, T.B., Chandru, U.V.[Uma V.],
Archiving Mural Paintings Using an Ontology Based Approach,
eHeritage12(II:37-48).
Springer DOI 1304
BibRef

Tanimoto, T.[Tetsushi], Horiuchi, T.[Takahiko], Tominaga, S.[Shoji],
Precise Estimation of Painting Surfaces for Digital Archiving,
CCIW13(171-183).
Springer DOI 1304
BibRef

Yamagishi, M.[Misako], Kubo, C.[Chiho], Yamaba, K.[Kazuo],
Considerations of the Affective Factors for Appreciating a Printed-Color Picture,
CCIW13(80-89).
Springer DOI 1304
BibRef

Okazawa, G.[Gouki], Komatsu, H.[Hidehiko],
Image Statistics for Golden Appearance of a Painting by a Japanese Edo-era Artist Jakuchu Ito,
CCIW13(68-79).
Springer DOI 1304
BibRef

Wang, Y.[Ying], Takatsuka, M.,
A Framework Towards Quantified Artistic Influences Analysis,
DICTA12(1-8).
IEEE DOI 1303
BibRef

Arora, R.S.[Ravneet Singh], Elgammal, A.[Ahmed],
Towards automated classification of fine-art painting style: A comparative study,
ICPR12(3541-3544).
WWW Link. 1302
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Sener, F.[Fadime], Samet, N.[Nermin], Sahin, P.D.[Pinar Duygulu],
Identification of Illustrators,
VISART12(I: 589-597).
Springer DOI 1210
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Gancarczyk, J.[Joanna],
Feature Vector Definition for a Decision Tree Based Craquelure Identification in Old Paintings,
VISART12(I: 542-550).
Springer DOI 1210
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Carneiro, G.[Gustavo], da Silva, N.P.[Nuno Pinho], del Bue, A.[Alessio], Costeira, J.P.[João Paulo],
Artistic Image Classification: An Analysis on the PRINTART Database,
ECCV12(IV: 143-157).
Springer DOI 1210
BibRef

Constable, M., Zhang, X.Y.[Xiao-Yan],
Depth-based Analyses of Landscape Paintings and Photographs According to Itten's Contrasts,
PSIVT10(481-486).
IEEE DOI 1011
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Sun, Y.H.[Yu-Hong], Wang, J.[Jiatao],
Representation of watercolor based on regions,
IASP11(496-500).
IEEE DOI 1112
BibRef

Landi, M.[Marco], Maino, G.[Giuseppe],
Multispectral Imaging and Digital Restoration for Paintings Documentation,
CIAP11(II: 464-474).
Springer DOI 1109
BibRef

Monti, M.[Mariapaola], Maino, G.[Giuseppe],
Image Processing and a Virtual Restoration Hypothesis for Mosaics and Their Cartoons,
CIAP11(II: 486-495).
Springer DOI 1109
BibRef

Barazzetti, L., Scaioni, M., Brumana, R., Remondino, F., Rizzi, A., Lo Brutto, M.,
Geometric and Radiometric Analysis of Paintings,
CloseRange10(xx-yy).
PDF File. 1006
BibRef

Schmidt, N., Schütze, R.[Rainer], Boochs, F.[Frank],
3D-Sutra: Interactive Analysis Tool For A Web-Atlas of Scanned Sutra Inscriptions In China,
CloseRange10(xx-yy).
PDF File. 1006
BibRef

Yao, L.[Lei], Li, J.[Jia], Wang, J.Z.[James Z.],
Characterizing elegance of curves computationally for distinguishing Morrisseau paintings and the imitations,
ICIP09(73-76).
IEEE DOI 0911
BibRef

Zhang, Q.[Qing],
Virtual Presenting a Famous Chinese Landscape Painting Based on Textured 3-D Model,
CISP09(1-4).
IEEE DOI 0910
BibRef

Tanaka, N., Tominaga, S.,
Multispectral Analysis of Oil Paintings and Data Compression,
Southwest06(158-162).
IEEE DOI 0603
BibRef

Tominaga, S., Tanaka, N., Komada, T.,
Estimation of surface properties of art paintings using a multi-band camera,
ICPR04(I: 92-95).
IEEE DOI 0409
BibRef
And:
Imaging and rendering of oil paintings using a multi-band camera,
Southwest04(6-10).
IEEE DOI 0411
BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Brush Stroke Analysis .


Last update:Sep 19, 2021 at 21:11:01