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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title | An Iterative Multiresolution Scheme for SFM with Missing Data: single and multiple object scenes | Type | Journal Article | ||
| Year | 2010 | Publication | Image and Vision Computing | Abbreviated Journal | IMAVIS |
| Volume | 28 | Issue | 1 | Pages | 164-176 |
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| Abstract | Most of the techniques proposed for tackling the Structure from Motion problem (SFM) cannot deal with high percentages of missing data in the matrix of trajectories. Furthermore, an additional problem should be faced up when working with multiple object scenes: the rank of the matrix of trajectories should be estimated. This paper presents an iterative multiresolution scheme for SFM with missing data to be used in both the single and multiple object cases. The proposed scheme aims at recovering missing entries in the original input matrix. The objective is to improve the results by applying a factorization technique to the partially or totally filled in matrix instead of to the original input one. Experimental results obtained with synthetic and real data sequences, containing single and multiple objects, are presented to show the viability of the proposed approach. | ||||
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| ISSN | 0262-8856 | ISBN | Medium | ||
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| Notes | ADAS | Approved | no | ||
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ADAS @ adas @ JSL2010 | Serial | 1278 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title | Predicting Missing Ratings in Recommender Systems: Adapted Factorization Approach | Type | Journal Article | ||
| Year | 2009 | Publication | International Journal of Electronic Commerce | Abbreviated Journal | |
| Volume | 14 | Issue | 1 | Pages | 89-108 |
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| Abstract | The paper presents a factorization-based approach to make predictions in recommender systems. These systems are widely used in electronic commerce to help customers find products according to their preferences. Taking into account the customer's ratings of some products available in the system, the recommender system tries to predict the ratings the customer would give to other products in the system. The proposed factorization-based approach uses all the information provided to compute the predicted ratings, in the same way as approaches based on Singular Value Decomposition (SVD). The main advantage of this technique versus SVD-based approaches is that it can deal with missing data. It also has a smaller computational cost. Experimental results with public data sets are provided to show that the proposed adapted factorization approach gives better predicted ratings than a widely used SVD-based approach. | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1086-4415 | ISBN | Medium | ||
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| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ JSL2009b | Serial | 1237 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title | An iterative multiresolution scheme for SFM with missing data | Type | Journal Article | ||
| Year | 2009 | Publication | Journal of Mathematical Imaging and Vision | Abbreviated Journal | JMIV |
| Volume | 34 | Issue | 3 | Pages | 240–258 |
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| Abstract | Several techniques have been proposed for tackling the Structure from Motion problem through factorization in the case of missing data. However, when the percentage of unknown data is high, most of them may not perform as well as expected. Focussing on this problem, an iterative multiresolution scheme, which aims at recovering missing entries in the originally given input matrix, is proposed. Information recovered following a coarse-to-fine strategy is used for filling in the missing entries. The objective is to recover, as much as possible, missing data in the given matrix.
Thus, when a factorization technique is applied to the partially or totally filled in matrix, instead of to the originally given input one, better results will be obtained. An evaluation study about the robustness to missing and noisy data is reported. Experimental results obtained with synthetic and real video sequences are presented to show the viability of the proposed approach. |
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| Notes | ADAS | Approved | no | ||
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ADAS @ adas @ JSL2009a | Serial | 1163 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title | An Adapted Alternation Approach for Recommender Systems | Type | Conference Article | ||
| Year | 2008 | Publication | IEEE International Conference on e–Business Engineering, | Abbreviated Journal | |
| Volume | Issue | Pages | 128–135 | ||
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| Abstract | This paper presents an adaptation of the alternation technique to tackle the prediction task in recommender systems. These systems are widely considered in electronic commerce to help customers to find products they will probably like or dislike. As the SVD-based approaches, the proposed adapted alternation technique uses all the information stored in the system to find the predictions. The main advantage of this technique with respect to the SVD-based ones is that it can deal with missing data. Furthermore, it has a smaller computational cost. Experimental results with public data sets are provided in order to show the viability of the proposed adapted alternation approach. | ||||
| Address | Xi’an (Xina) | ||||
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| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ JSL2008e | Serial | 1044 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat | ||||
| Title | Photometric Stereo through and Adapted Alternation Approach | Type | Conference Article | ||
| Year | 2008 | Publication | IEEE International Conference on Image Processing, | Abbreviated Journal | |
| Volume | Issue | Pages | 1500–1503 | ||
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| Address | San Diego; CA; USA | ||||
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| Notes | ADAS | Approved | no | ||
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ADAS @ adas @ JSL2008d | Serial | 1016 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Antonio Lopez | ||||
| Title | Recovery of Surface Normals and Reflectance from Different Lighting Conditions | Type | Conference Article | ||
| Year | 2008 | Publication | 5th International Conference on Image Analysis and Recognition | Abbreviated Journal | |
| Volume | 5112 | Issue | Pages | 315–325 | |
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| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
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| Notes | ADAS | Approved | no | ||
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ADAS @ adas @ JSL2008c | Serial | 1014 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras | ||||
| Title | Aprendiendo a recrear la realidad en 3D | Type | Journal | ||
| Year | 2008 | Publication | UAB Divulga, Revista de divulgacion cientifica | Abbreviated Journal | |
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| Notes | spreading;ADAS | Approved | no | ||
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ADAS @ adas @ JSL2008b | Serial | 1472 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title | Rank Estimation in 3D Multibody Motion Segmentation | Type | Journal Article | ||
| Year | 2008 | Publication | Electronic Letters | Abbreviated Journal | |
| Volume | 44 | Issue | 4 | Pages | 279-280 |
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| Abstract | A novel technique for rank estimation in 3D multibody motion segmentation is proposed. It is based on the study of the frequency spectra of moving rigid objects and does not use or assume a prior knowledge of the objects contained in the scene (i.e. number of objects and motion). The significance of rank estimation on multibody motion segmentation results is shown by using two motion segmentation algorithms over both synthetic and real data. | ||||
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| Notes | ADAS | Approved | no | ||
| Call Number |
ADAS @ adas @ JSL2008a | Serial | 939 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title | Motion Segmentation from Feature Trajectories with Missing Data | Type | Conference Article | ||
| Year | 2007 | Publication | 3rd. Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | IbPRIA 2007 |
| Volume | LNCS 4477 | Issue | Pages | 483–490 | |
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| Address | Girona (Spain) | ||||
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| Publisher | Place of Publication | Editor | J. Marti et al. (Eds.) | ||
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| Notes | ADAS | Approved | no | ||
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ADAS @ adas @ JSL2007a | Serial | 814 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title | An Iterative Multiresolution Scheme for SFM | Type | Conference Article | ||
| Year | 2006 | Publication | International Conference on Image Analysis and Recognition | Abbreviated Journal | ICIAR 2006 |
| Volume | LNCS 4141 | Issue | 1 | Pages | 804–815 |
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| Notes | ADAS | Approved | no | ||
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ADAS @ adas @ JSL2006c | Serial | 704 | ||
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| Author | Carme Julia; Angel Sappa; Felipe Lumbreras; Joan Serrat; Antonio Lopez | ||||
| Title | Factorization with Missing and Noisy Data | Type | Conference Article | ||
| Year | 2006 | Publication | 6th International Conference on Computational Science | Abbreviated Journal | ICCS´06 |
| Volume | LNCS 3991 | Issue | Pages | 555–562 | |
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| Address | Reading (United Kingdom) | ||||
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| Notes | ADAS | Approved | no | ||
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ADAS @ adas @ JSL2006b | Serial | 653 | ||
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| Author | Carme Julia; Joan Serrat; Antonio Lopez; Felipe Lumbreras; Daniel Ponsa | ||||
| Title | Motion segmentation through factorization. Application to night driving assistance | Type | Miscellaneous | ||
| Year | 2006 | Publication | International Conference on Computer Vision Theory and Applications, (2) | Abbreviated Journal | |
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| Notes | ADAS | Approved | no | ||
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ADAS @ adas @ JSL2006a | Serial | 638 | ||
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| Author | Javier Jimenez; Antonio Lopez; Joan Serrat | ||||
| Title | Un enfoque ABP aplicado a Ingenieria del Software | Type | Miscellaneous | ||
| Year | 2007 | Publication | Seminario Internacional RED–U 2–07 para El desarrollo de la autonomia en el aprendizaje | Abbreviated Journal | |
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| Address | Barcelona (Spain) | ||||
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| Notes | ADAS | Approved | no | ||
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ADAS @ adas @ JLS2007 | Serial | 937 | ||
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| Author | Simon Jégou; Michal Drozdzal; David Vazquez; Adriana Romero; Yoshua Bengio | ||||
| Title | The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation | Type | Conference Article | ||
| Year | 2017 | Publication | IEEE Conference on Computer Vision and Pattern Recognition Workshops | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Semantic Segmentation | ||||
| Abstract | State-of-the-art approaches for semantic image segmentation are built on Convolutional Neural Networks (CNNs). The typical segmentation architecture is composed of (a) a downsampling path responsible for extracting coarse semantic features, followed by (b) an upsampling path trained to recover the input image resolution at the output of the model and, optionally, (c) a post-processing module (e.g. Conditional Random Fields) to refine the model predictions.
Recently, a new CNN architecture, Densely Connected Convolutional Networks (DenseNets), has shown excellent results on image classification tasks. The idea of DenseNets is based on the observation that if each layer is directly connected to every other layer in a feed-forward fashion then the network will be more accurate and easier to train. In this paper, we extend DenseNets to deal with the problem of semantic segmentation. We achieve state-of-the-art results on urban scene benchmark datasets such as CamVid and Gatech, without any further post-processing module nor pretraining. Moreover, due to smart construction of the model, our approach has much less parameters than currently published best entries for these datasets. |
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| Address | Honolulu; USA; July 2017 | ||||
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| Area | Expedition | Conference | CVPRW | ||
| Notes | MILAB; ADAS; 600.076; 600.085; 601.281 | Approved | no | ||
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ADAS @ adas @ JDV2016 | Serial | 2866 | ||
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| Author | Yu Jie; Jaume Amores; N. Sebe; Petia Radeva; Tian Qi | ||||
| Title | Distance Learning for Similarity Estimation | Type | Journal | ||
| Year | 2008 | Publication | IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.30(3):451–462 | Abbreviated Journal | |
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| Notes | ADAS;MILAB | Approved | no | ||
| Call Number |
ADAS @ adas @ JAS2008 | Serial | 961 | ||
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