toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier edit   pdf
doi  openurl
  Title An active contour model for speech balloon detection in comics Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1240-1244  
  Keywords  
  Abstract Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent comic book understanding would enable a variety of new applications, including content-based retrieval and content retargeting. Document understanding in this domain is challenging as comics are semi-structured documents, combining semantically important graphical and textual parts. Few studies have been done in this direction. In this work we detail a novel approach for closed and non-closed speech balloon localization in scanned comic book pages, an essential step towards a fully automatic comic book understanding. The approach is compared with existing methods for closed balloon localization found in the literature and results are presented.  
  Address washington; USA; August 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1520-5363 ISBN Medium  
  Area Expedition Conference (down) ICDAR  
  Notes DAG; CIC; 600.056 Approved no  
  Call Number Admin @ si @ RKW2013a Serial 2260  
Permanent link to this record
 

 
Author Alicia Fornes; Xavier Otazu; Josep Llados edit   pdf
doi  openurl
  Title Show through cancellation and image enhancement by multiresolution contrast processing Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 200-204  
  Keywords  
  Abstract Historical documents suffer from different types of degradation and noise such as background variation, uneven illumination or dark spots. In case of double-sided documents, another common problem is that the back side of the document usually interferes with the front side because of the transparency of the document or ink bleeding. This effect is called the show through phenomenon. Many methods are developed to solve these problems, and in the case of show-through, by scanning and matching both the front and back sides of the document. In contrast, our approach is designed to use only one side of the scanned document. We hypothesize that show-trough are low contrast components, while foreground components are high contrast ones. A Multiresolution Contrast (MC) decomposition is presented in order to estimate the contrast of features at different spatial scales. We cancel the show-through phenomenon by thresholding these low contrast components. This decomposition is also able to enhance the image removing shadowed areas by weighting spatial scales. Results show that the enhanced images improve the readability of the documents, allowing scholars both to recover unreadable words and to solve ambiguities.  
  Address Washington; USA; August 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1520-5363 ISBN Medium  
  Area Expedition Conference (down) ICDAR  
  Notes DAG; 602.006; 600.045; 600.061; 600.052;CIC Approved no  
  Call Number Admin @ si @ FOL2013 Serial 2241  
Permanent link to this record
 

 
Author Ivet Rafegas; Maria Vanrell edit   pdf
openurl 
  Title Color representation in CNNs: parallelisms with biological vision Type Conference Article
  Year 2017 Publication ICCV Workshop on Mutual Benefits ofr Cognitive and Computer Vision Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Convolutional Neural Networks (CNNs) trained for object recognition tasks present representational capabilities approaching to primate visual systems [1]. This provides a computational framework to explore how image features
are efficiently represented. Here, we dissect a trained CNN
[2] to study how color is represented. We use a classical methodology used in physiology that is measuring index of selectivity of individual neurons to specific features. We use ImageNet Dataset [20] images and synthetic versions
of them to quantify color tuning properties of artificial neurons to provide a classification of the network population.
We conclude three main levels of color representation showing some parallelisms with biological visual systems: (a) a decomposition in a circular hue space to represent single color regions with a wider hue sampling beyond the first
layer (V2), (b) the emergence of opponent low-dimensional spaces in early stages to represent color edges (V1); and (c) a strong entanglement between color and shape patterns representing object-parts (e.g. wheel of a car), objectshapes (e.g. faces) or object-surrounds configurations (e.g. blue sky surrounding an object) in deeper layers (V4 or IT).
 
  Address Venice; Italy; October 2017  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) ICCV-MBCC  
  Notes CIC; 600.087; 600.051 Approved no  
  Call Number Admin @ si @ RaV2017 Serial 2984  
Permanent link to this record
 

 
Author Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell edit  url
doi  isbn
openurl 
  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  
  Keywords  
  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  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1550-5499 ISBN 978-1-4244-4420-5 Medium  
  Area Expedition Conference (down) ICCV  
  Notes CIC Approved no  
  Call Number CAT @ cat @ SWV2009 Serial 1196  
Permanent link to this record
 

 
Author Shida Beigpour; Joost Van de Weijer edit   pdf
url  doi
isbn  openurl
  Title Object Recoloring Based on Intrinsic Image Estimation Type Conference Article
  Year 2011 Publication 13th IEEE International Conference in Computer Vision Abbreviated Journal  
  Volume Issue Pages 327 - 334  
  Keywords  
  Abstract Object recoloring is one of the most popular photo-editing tasks. The problem of object recoloring is highly under-constrained, and existing recoloring methods limit their application to objects lit by a white illuminant. Application of these methods to real-world scenes lit by colored illuminants, multiple illuminants, or interreflections, results in unrealistic recoloring of objects. In this paper, we focus on the recoloring of single-colored objects presegmented from their background. The single-color constraint allows us to fit a more comprehensive physical model to the object. We demonstrate that this permits us to perform realistic recoloring of objects lit by non-white illuminants, and multiple illuminants. Moreover, the model allows for more realistic handling of illuminant alteration of the scene. Recoloring results captured by uncalibrated cameras demonstrate that the proposed framework obtains realistic recoloring for complex natural images. Furthermore we use the model to transfer color between objects and show that the results are more realistic than existing color transfer methods.  
  Address Barcelona  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1550-5499 ISBN 978-1-4577-1101-5 Medium  
  Area Expedition Conference (down) ICCV  
  Notes CIC Approved no  
  Call Number Admin @ si @ BeW2011 Serial 1781  
Permanent link to this record
 

 
Author Danna Xue; Luis Herranz; Javier Vazquez; Yanning Zhang edit  url
doi  openurl
  Title Burst Perception-Distortion Tradeoff: Analysis and Evaluation Type Conference Article
  Year 2023 Publication IEEE International Conference on Acoustics, Speech and Signal Processing Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Burst image restoration attempts to effectively utilize the complementary cues appearing in sequential images to produce a high-quality image. Most current methods use all the available images to obtain the reconstructed image. However, using more images for burst restoration is not always the best option regarding reconstruction quality and efficiency, as the images acquired by handheld imaging devices suffer from degradation and misalignment caused by the camera noise and shake. In this paper, we extend the perception-distortion tradeoff theory by introducing multiple-frame information. We propose the area of the unattainable region as a new metric for perception-distortion tradeoff evaluation and comparison. Based on this metric, we analyse the performance of burst restoration from the perspective of the perception-distortion tradeoff under both aligned bursts and misaligned bursts situations. Our analysis reveals the importance of inter-frame alignment for burst restoration and shows that the optimal burst length for the restoration model depends both on the degree of degradation and misalignment.  
  Address Rodhes Islands; Greece; June 2023  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) ICASSP  
  Notes CIC; MACO Approved no  
  Call Number Admin @ si @ XHV2023 Serial 3909  
Permanent link to this record
 

 
Author Fernando Lopez; J.M. Valiente; Ramon Baldrich; Maria Vanrell edit  doi
openurl 
  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  
  Keywords  
  Abstract  
  Address Germany  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor LNCS Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) IbPRIA  
  Notes CIC Approved no  
  Call Number CAT @ cat @ LVB2005 Serial 641  
Permanent link to this record
 

 
Author Sandra Jimenez; Xavier Otazu; Valero Laparra; Jesus Malo edit   pdf
doi  openurl
  Title Chromatic induction and contrast masking: similar models, different goals? Type Conference Article
  Year 2013 Publication Human Vision and Electronic Imaging XVIII Abbreviated Journal  
  Volume 8651 Issue Pages  
  Keywords  
  Abstract Normalization of signals coming from linear sensors is an ubiquitous mechanism of neural adaptation.1 Local interaction between sensors tuned to a particular feature at certain spatial position and neighbor sensors explains a wide range of psychophysical facts including (1) masking of spatial patterns, (2) non-linearities of motion sensors, (3) adaptation of color perception, (4) brightness and chromatic induction, and (5) image quality assessment. Although the above models have formal and qualitative similarities, it does not necessarily mean that the mechanisms involved are pursuing the same statistical goal. For instance, in the case of chromatic mechanisms (disregarding spatial information), different parameters in the normalization give rise to optimal discrimination or adaptation, and different non-linearities may give rise to error minimization or component independence. In the case of spatial sensors (disregarding color information), a number of studies have pointed out the benefits of masking in statistical independence terms. However, such statistical analysis has not been performed for spatio-chromatic induction models where chromatic perception depends on spatial configuration. In this work we investigate whether successful spatio-chromatic induction models,6 increase component independence similarly as previously reported for masking models. Mutual information analysis suggests that seeking an efficient chromatic representation may explain the prevalence of induction effects in spatially simple images. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.  
  Address San Francisco CA; USA; February 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) HVEI  
  Notes CIC Approved no  
  Call Number Admin @ si @ JOL2013 Serial 2240  
Permanent link to this record
 

 
Author Partha Pratim Roy; Eduard Vazquez; Josep Llados; Ramon Baldrich; Umapada Pal edit  openurl
  Title A System to Retrieve Text/Symbols from Color Maps using Connected Component and Skeleton Analysis Type Conference Article
  Year 2007 Publication Seventh IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages 79–78  
  Keywords  
  Abstract  
  Address Curitiba (Brasil)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor J. Llados, W. Liu, J.M. Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) GREC  
  Notes CAT; DAG;CIC Approved no  
  Call Number CAT @ cat @ RVL2007 Serial 836  
Permanent link to this record
 

 
Author Olivier Penacchio; Laura Dempere-Marco; Xavier Otazu edit   pdf
openurl 
  Title A Neurodynamical Model Of Brightness Induction In V1 Following Static And Dynamic Contextual Influences Type Abstract
  Year 2012 Publication 8th Federation of European Neurosciences Abbreviated Journal  
  Volume 6 Issue Pages 63-64  
  Keywords  
  Abstract Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Although striate cortex is traditionally regarded as an area mostly responsive to ensory (i.e. retinal) information,
neurophysiological evidence suggests that perceived brightness information mightbe explicitly represented in V1.
Such evidence has been observed both in anesthetised cats where neuronal response modulations have been found to follow luminance changes outside the receptive felds and in human fMRI measurements. In this work, possible neural mechanisms that ofer a plausible explanation for such phenomenon are investigated. To this end, we consider the model proposed by Z.Li (Li, Network:Comput. Neural Syst., 10 (1999)) which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual infuences, i.e. layer 2-3 pyramidal cells, interneurons, and horizontal intracortical connections. This model has reproduced other phenomena such as contour detection and preattentive segmentation, which share with brightness induction the relevant efect of contextual infuences. We have extended the original model such that the input to the network is obtained from a complete multiscale and multiorientation wavelet decomposition, thereby allowing the recovery of an image refecting the perceived intensity. The proposed model successfully accounts for well known psychophysical efects for static contexts (among them: the White's and modifed White's efects, the Todorovic, Chevreul, achromatic ring patterns, and grating induction efects) and also for brigthness induction in dynamic contexts defned by modulating the luminance of surrounding areas (e.g. the brightness of a static central area is perceived to vary in antiphase to the sinusoidal luminance changes of its surroundings). This work thus suggests that intra-cortical interactions in V1 could partially explain perceptual brightness induction efects and reveals how a common general architecture may account for several different fundamental processes emerging early in the visual processing pathway.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) FENS  
  Notes CIC Approved no  
  Call Number Admin @ si @ PDO2012b Serial 2181  
Permanent link to this record
 

 
Author Jordi Roca; C. Alejandro Parraga; Maria Vanrell edit  url
openurl 
  Title Categorical Focal Colours are Structurally Invariant Under Illuminant Changes Type Conference Article
  Year 2011 Publication European Conference on Visual Perception Abbreviated Journal  
  Volume Issue Pages 196  
  Keywords  
  Abstract The visual system perceives the colour of surfaces approximately constant under changes of illumination. In this work, we investigate how stable is the perception of categorical \“focal\” colours and their interrelations with varying illuminants and simple chromatic backgrounds. It has been proposed that best examples of colour categories across languages cluster in small regions of the colour space and are restricted to a set of 11 basic terms (Kay and Regier, 2003 Proceedings of the National Academy of Sciences of the USA 100 9085\–9089). Following this, we developed a psychophysical paradigm that exploits the ability of subjects to reliably reproduce the most representative examples of each category, adjusting multiple test patches embedded in a coloured Mondrian. The experiment was run on a CRT monitor (inside a dark room) under various simulated illuminants. We modelled the recorded data for each subject and adapted state as a 3D interconnected structure (graph) in Lab space. The graph nodes were the subject\’s focal colours at each adaptation state. The model allowed us to get a better distance measure between focal structures under different illuminants. We found that perceptual focal structures tend to be preserved better than the structures of the physical \“ideal\” colours under illuminant changes.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Perception 40 Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) ECVP  
  Notes CIC Approved no  
  Call Number Admin @ si @ RPV2011 Serial 1867  
Permanent link to this record
 

 
Author Xim Cerda-Company; C. Alejandro Parraga; Xavier Otazu edit  openurl
  Title Which tone-mapping is the best? A comparative study of tone-mapping perceived quality Type Abstract
  Year 2014 Publication Perception Abbreviated Journal  
  Volume 43 Issue Pages 106  
  Keywords  
  Abstract Perception 43 ECVP Abstract Supplement
High-dynamic-range (HDR) imaging refers to the methods designed to increase the brightness dynamic range present in standard digital imaging techniques. This increase is achieved by taking the same picture under di erent exposure values and mapping the intensity levels into a single image by way of a tone-mapping operator (TMO). Currently, there is no agreement on how to evaluate the quality
of di erent TMOs. In this work we psychophysically evaluate 15 di erent TMOs obtaining rankings based on the perceived properties of the resulting tone-mapped images. We performed two di erent experiments on a CRT calibrated display using 10 subjects: (1) a study of the internal relationships between grey-levels and (2) a pairwise comparison of the resulting 15 tone-mapped images. In (1) observers internally matched the grey-levels to a reference inside the tone-mapped images and in the real scene. In (2) observers performed a pairwise comparison of the tone-mapped images alongside the real scene. We obtained two rankings of the TMOs according their performance. In (1) the best algorithm
was ICAM by J.Kuang et al (2007) and in (2) the best algorithm was a TMO by Krawczyk et al (2005). Our results also show no correlation between these two rankings.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) ECVP  
  Notes CIC; NEUROBIT; 600.074 Approved no  
  Call Number Admin @ si @ CPO2014 Serial 2527  
Permanent link to this record
 

 
Author Olivier Penacchio; Xavier Otazu; A. wilkins; J. Harris edit  url
openurl 
  Title Uncomfortable images prevent lateral interactions in the cortex from providing a sparse code Type Conference Article
  Year 2015 Publication European Conference on Visual Perception ECVP2015 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Liverpool; uk; August 2015  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) ECVP  
  Notes NEUROBIT;CIC Approved no  
  Call Number Admin @ si @ POW2015 Serial 2633  
Permanent link to this record
 

 
Author Ivet Rafegas; Maria Vanrell edit  openurl
  Title Colour Visual Coding in trained Deep Neural Networks Type Abstract
  Year 2016 Publication European Conference on Visual Perception Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Barcelona; Spain; August 2016  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) ECVP  
  Notes CIC Approved no  
  Call Number Admin @ si @ RaV2016b Serial 2895  
Permanent link to this record
 

 
Author Eduard Vazquez; Joost Van de Weijer; Ramon Baldrich edit  openurl
  Title Image Segmentation in the Presence of Shadows and Highligts Type Conference Article
  Year 2008 Publication 10th European Conference on Computer Vision Abbreviated Journal  
  Volume 5305 Issue Pages 1–14  
  Keywords  
  Abstract  
  Address Marseille (France)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) ECCV  
  Notes CAT;CIC Approved no  
  Call Number CAT @ cat @ VVB2008b Serial 1013  
Permanent link to this record
 

 
Author Jaime Moreno; Xavier Otazu edit  openurl
  Title Image coder based on Hilbert scanning of embedded quadTrees Type Conference Article
  Year 2011 Publication Data Compression Conference Abbreviated Journal  
  Volume Issue Pages 470-470  
  Keywords  
  Abstract In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) DCC  
  Notes CIC Approved no  
  Call Number Admin @ si @ MoO2011b Serial 2177  
Permanent link to this record
 

 
Author Bojana Gajic; Ariel Amato; Ramon Baldrich; Joost Van de Weijer; Carlo Gatta edit   pdf
doi  openurl
  Title Area Under the ROC Curve Maximization for Metric Learning Type Conference Article
  Year 2022 Publication CVPR 2022 Workshop on Efficien Deep Learning for Computer Vision (ECV 2022, 5th Edition) Abbreviated Journal  
  Volume Issue Pages  
  Keywords Training; Computer vision; Conferences; Area measurement; Benchmark testing; Pattern recognition  
  Abstract Most popular metric learning losses have no direct relation with the evaluation metrics that are subsequently applied to evaluate their performance. We hypothesize that training a metric learning model by maximizing the area under the ROC curve (which is a typical performance measure of recognition systems) can induce an implicit ranking suitable for retrieval problems. This hypothesis is supported by previous work that proved that a curve dominates in ROC space if and only if it dominates in Precision-Recall space. To test this hypothesis, we design and maximize an approximated, derivable relaxation of the area under the ROC curve. The proposed AUC loss achieves state-of-the-art results on two large scale retrieval benchmark datasets (Stanford Online Products and DeepFashion In-Shop). Moreover, the AUC loss achieves comparable performance to more complex, domain specific, state-of-the-art methods for vehicle re-identification.  
  Address New Orleans, USA; 20 June 2022  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) CVPRW  
  Notes CIC; LAMP; Approved no  
  Call Number Admin @ si @ GAB2022 Serial 3700  
Permanent link to this record
 

 
Author Bojana Gajic; Ramon Baldrich edit  doi
openurl 
  Title Cross-domain fashion image retrieval Type Conference Article
  Year 2018 Publication CVPR 2018 Workshop on Women in Computer Vision (WiCV 2018, 4th Edition) Abbreviated Journal  
  Volume Issue Pages 19500-19502  
  Keywords  
  Abstract Cross domain image retrieval is a challenging task that implies matching images from one domain to their pairs from another domain. In this paper we focus on fashion image retrieval, which involves matching an image of a fashion item taken by users, to the images of the same item taken in controlled condition, usually by professional photographer. When facing this problem, we have different products
in train and test time, and we use triplet loss to train the network. We stress the importance of proper training of simple architecture, as well as adapting general models to the specific task.
 
  Address Salt Lake City, USA; 22 June 2018  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (down) CVPRW  
  Notes CIC; 600.087 Approved no  
  Call Number Admin @ si @ Serial 3709  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: