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Author | Hassan Ahmed Sial; Ramon Baldrich; Maria Vanrell |
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Title | Deep intrinsic decomposition trained on surreal scenes yet with realistic light effects | Type | Journal Article | |||
Year | 2020 | Publication | Journal of the Optical Society of America A | Abbreviated Journal | JOSA A | |
Volume | 37 | Issue | 1 | Pages | 1-15 | |
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Abstract | Estimation of intrinsic images still remains a challenging task due to weaknesses of ground-truth datasets, which either are too small or present non-realistic issues. On the other hand, end-to-end deep learning architectures start to achieve interesting results that we believe could be improved if important physical hints were not ignored. In this work, we present a twofold framework: (a) a flexible generation of images overcoming some classical dataset problems such as larger size jointly with coherent lighting appearance; and (b) a flexible architecture tying physical properties through intrinsic losses. Our proposal is versatile, presents low computation time, and achieves state-of-the-art results. | |||||
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Notes | CIC; 600.140; 600.12; 600.118 | Approved | no | |||
Call Number | Admin @ si @ SBV2019 | Serial | 3311 | |||
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Author | Graham D. Finlayson; Javier Vazquez; Sabine Süsstrunk; Maria Vanrell |
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Title | Spectral sharpening by spherical sampling | Type | Journal Article | |||
Year | 2012 | Publication | Journal of the Optical Society of America A | Abbreviated Journal | JOSA A | |
Volume | 29 | Issue | 7 | Pages | 1199-1210 | |
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Abstract | There are many works in color that assume illumination change can be modeled by multiplying sensor responses by individual scaling factors. The early research in this area is sometimes grouped under the heading “von Kries adaptation”: the scaling factors are applied to the cone responses. In more recent studies, both in psychophysics and in computational analysis, it has been proposed that scaling factors should be applied to linear combinations of the cones that have narrower support: they should be applied to the so-called “sharp sensors.” In this paper, we generalize the computational approach to spectral sharpening in three important ways. First, we introduce spherical sampling as a tool that allows us to enumerate in a principled way all linear combinations of the cones. This allows us to, second, find the optimal sharp sensors that minimize a variety of error measures including CIE Delta E (previous work on spectral sharpening minimized RMS) and color ratio stability. Lastly, we extend the spherical sampling paradigm to the multispectral case. Here the objective is to model the interaction of light and surface in terms of color signal spectra. Spherical sampling is shown to improve on the state of the art. | |||||
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ISSN | 1084-7529 | ISBN | Medium | |||
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Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ FVS2012 | Serial | 2000 | |||
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Author | Francesc Tous; Maria Vanrell; Ramon Baldrich |
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Title | Exploring Colour Constancy Solutions. | Type | Miscellaneous | |||
Year | 2004 | Publication | CGIV 2004 Second European Conference on Colour in Graphics, Imaging, and Vision, 24:29 | Abbreviated Journal | ||
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Address | Aachen (Germany) | |||||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ TVB2004 | Serial | 452 | |||
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Author | Francesc Tous; Maria Vanrell; Ramon Baldrich |
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Title | Relaxed Grey-World: Computational Colour Constancy by Surface Matching | Type | Book Chapter | |||
Year | 2005 | Publication | Pattern Recognition and Image Analysis (IbPRIA 2005), LNCS 3522:192–199 | Abbreviated Journal | ||
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Address | Estoril (Portugal) | |||||
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Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ TVB2005 | Serial | 555 | |||
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Author | Francesc Tous; Agnes Borras; Robert Benavente; Ramon Baldrich; Maria Vanrell; Josep Llados |
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Title | Textual Descriptors for browsing people by visual appearence. | Type | Conference Article | |||
Year | 2002 | Publication | 5è. Congrés Català d’Intel·ligència Artificial CCIA | Abbreviated Journal | ||
Volume | Issue | Pages | ||||
Keywords | Image retrieval, textual descriptors, colour naming, colour normalization, graph matching. | |||||
Abstract | This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building. | |||||
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Notes | DAG;CIC | Approved | no | |||
Call Number | CAT @ cat @ TBB2002a | Serial | 287 | |||
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Author | Francesc Tous; Agnes Borras; Robert Benavente; Ramon Baldrich; Maria Vanrell; Josep Llados |
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Title | Textual Descriptions for Browsing People by Visual Apperance. | Type | Book Chapter | |||
Year | 2002 | Publication | Lecture Notes in Artificial Intelligence | Abbreviated Journal | ||
Volume | 2504 | Issue | Pages | 419-429 | ||
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Abstract | This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building | |||||
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Publisher | Springer Verlag | Place of Publication | Editor | |||
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Notes | DAG;CIC | Approved | no | |||
Call Number | CAT @ cat @ TBB2002b | Serial | 319 | |||
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Author | Fernando Lopez; J.M. Valiente; Ramon Baldrich; Maria Vanrell |
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Title | Fast surface grading using color statistics in the CIELab space | Type | Conference Article | |||
Year | 2005 | Publication | Pattern Recognition and Image Analysis. IbPRIA 2005 | Abbreviated Journal | ||
Volume | LNCS 3523 | Issue | Pages | 66-673 | ||
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Address | Germany | |||||
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Series Editor | LNCS | Series Title | Abbreviated Series Title | |||
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Area | Expedition | Conference | IbPRIA | |||
Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ LVB2005 | Serial | 641 | |||
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Author | Felipe Lumbreras; Ramon Baldrich; Maria Vanrell; Joan Serrat; Juan J. Villanueva |
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Title | Multiresolution colour texture representations for tile classification | Type | Miscellaneous | |||
Year | 1999 | Publication | Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes | Abbreviated Journal | ||
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Address | Bilbao | |||||
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Notes | ADAS;CIC | Approved | no | |||
Call Number | ADAS @ adas @ LBV1999a | Serial | 3 | |||
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Author | Felipe Lumbreras; Ramon Baldrich; Maria Vanrell; Joan Serrat; Juan J. Villanueva |
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Title | Multiresolution texture classification of ceramic tiles. | Type | Book Chapter | |||
Year | 1999 | Publication | Recent Research developments in optical engineering, Research Signpost, 2: 213–228 | Abbreviated Journal | ||
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Address | India | |||||
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Notes | ADAS;CIC | Approved | no | |||
Call Number | ADAS @ adas @ LBV1999b | Serial | 45 | |||
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Author | Felipe Lumbreras; Joan Serrat; Ramon Baldrich; Maria Vanrell; Juan J. Villanueva |
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Title | Color Texture Recognition Through Multiresolution Features | Type | Miscellaneous | |||
Year | 2001 | Publication | QCAV 2001 International Conference on Quality Control by Artificial Vision, France, 1:114–121. | Abbreviated Journal | ||
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Notes | ADAS;CIC | Approved | no | |||
Call Number | ADAS @ adas @ LSB2001 | Serial | 124 | |||
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Author | Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell; Antonio Lopez |
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Title | Color Attributes for Object Detection | Type | Conference Article | |||
Year | 2012 | Publication | 25th IEEE Conference on Computer Vision and Pattern Recognition | Abbreviated Journal | ||
Volume | Issue | Pages | 3306-3313 | |||
Keywords | pedestrian detection | |||||
Abstract | State-of-the-art object detectors typically use shape information as a low level feature representation to capture the local structure of an object. This paper shows that early fusion of shape and color, as is popular in image classification,
leads to a significant drop in performance for object detection. Moreover, such approaches also yields suboptimal results for object categories with varying importance of color and shape. In this paper we propose the use of color attributes as an explicit color representation for object detection. Color attributes are compact, computationally efficient, and when combined with traditional shape features provide state-ofthe- art results for object detection. Our method is tested on the PASCAL VOC 2007 and 2009 datasets and results clearly show that our method improves over state-of-the-art techniques despite its simplicity. We also introduce a new dataset consisting of cartoon character images in which color plays a pivotal role. On this dataset, our approach yields a significant gain of 14% in mean AP over conventional state-of-the-art methods. |
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Address | Providence; Rhode Island; USA; | |||||
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Publisher | IEEE Xplore | Place of Publication | Editor | |||
Language | Summary Language | Original Title | ||||
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ISSN | 1063-6919 | ISBN | 978-1-4673-1226-4 | Medium | ||
Area | Expedition | Conference | CVPR | |||
Notes | ADAS; CIC; | Approved | no | |||
Call Number | Admin @ si @ KRW2012 | Serial | 1935 | |||
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Author | Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
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Title | Top-Down Color Attention for Object Recognition | Type | Conference Article | |||
Year | 2009 | Publication | 12th International Conference on Computer Vision | Abbreviated Journal | ||
Volume | Issue | Pages | 979 - 986 | |||
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Abstract | Generally the bag-of-words based image representation follows a bottom-up paradigm. The subsequent stages of the process: feature detection, feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, combining multiple cues such as shape and color often provides below-expected results. This paper presents a novel method for recognizing object categories when using multiple cues by separating the shape and color cue. Color is used to guide attention by means of a top-down category-specific attention map. The color attention map is then further deployed to modulate the shape features by taking more features from regions within an image that are likely to contain an object instance. This procedure leads to a category-specific image histogram representation for each category. Furthermore, we argue that the method combines the advantages of both early and late fusion. We compare our approach with existing methods that combine color and shape cues on three data sets containing varied importance of both cues, namely, Soccer ( color predominance), Flower (color and shape parity), and PASCAL VOC Challenge 2007 (shape predominance). The experiments clearly demonstrate that in all three data sets our proposed framework significantly outperforms the state-of-the-art methods for combining color and shape information. | |||||
Address | Kyoto, Japan | |||||
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ISSN | 1550-5499 | ISBN | 978-1-4244-4420-5 | Medium | ||
Area | Expedition | Conference | ICCV | |||
Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ SWV2009 | Serial | 1196 | |||
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Author | Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
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Title | Who Painted this Painting? | Type | Conference Article | |||
Year | 2010 | Publication | Proceedings of The CREATE 2010 Conference | Abbreviated Journal | ||
Volume | Issue | Pages | 329–333 | |||
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Address | Gjovik (Norway) | |||||
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Area | Expedition | Conference | CREATE | |||
Notes | CIC | Approved | no | |||
Call Number | CAT @ cat @ KWV2010 | Serial | 1329 | |||
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Author | Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
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Title | Modulating Shape Features by Color Attention for Object Recognition | Type | Journal Article | |||
Year | 2012 | Publication | International Journal of Computer Vision | Abbreviated Journal | IJCV | |
Volume | 98 | Issue | 1 | Pages | 49-64 | |
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Abstract | Bag-of-words based image representation is a successful approach for object recognition. Generally, the subsequent stages of the process: feature detection,feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, it was found that the combination of different image cues, such as shape and color, often obtains below expected results. This paper presents a novel method for recognizing object categories when using ultiple cues by separately processing the shape and color cues and combining them by modulating the shape features by category specific color attention. Color is used to compute bottom up and top-down attention maps. Subsequently, these color attention maps are used to modulate the weights of the shape features. In regions with higher attention shape features are given more weight than in regions with low attention. We compare our approach with existing methods that combine color and shape cues on five data sets containing varied importance of both cues, namely, Soccer (color predominance), Flower (color and hape parity), PASCAL VOC 2007 and 2009 (shape predominance) and Caltech-101 (color co-interference). The experiments clearly demonstrate that in all five data sets our proposed framework significantly outperforms existing methods for combining color and shape information. | |||||
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Publisher | Springer Netherlands | Place of Publication | Editor | |||
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Series Volume | Series Issue | Edition | ||||
ISSN | 0920-5691 | ISBN | Medium | |||
Area | Expedition | Conference | ||||
Notes | CIC | Approved | no | |||
Call Number | Admin @ si @ KWV2012 | Serial | 1864 | |||
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