Zobrazeno 1 - 10
of 82
pro vyhledávání: '"François, Lauze"'
Publikováno v:
International Journal of Computer Vision. 131:1448-1476
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031319747
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a39ef295a40c46eab1fa9897133c6e43
https://doi.org/10.1007/978-3-031-31975-4_53
https://doi.org/10.1007/978-3-031-31975-4_53
Publikováno v:
Liu, R, Lauze, F, Erleben, K, Berg, R W & Darkner, S 2022, ' Bundle geodesic convolutional neural network for diffusion-weighted imaging segmentation ', Journal of Medical Imaging, vol. 9, no. 6, 064002 . https://doi.org/10.1117/1.JMI.9.6.064002
PurposeApplying machine learning techniques to magnetic resonance diffusion-weighted imaging (DWI) data is challenging due to the size of individual data samples and the lack of labeled data. It is possible, though, to learn general patterns from a v
Publikováno v:
Journal of Mathematical Imaging and Vision. 64:1-16
We present an information-theoretic approach to the registration of images with directional information, and especially for diffusion-Weighted Images (DWI), with explicit optimization over the directional scale. We call it Locally Orderless Registrat
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030755485
SSVM
SSVM
First Order Locally Orderless Registration (FLOR) is a scale-space framework for image density estimation used for defining image similarity, mainly for Image Registration. The Locally Orderless Registration framework was designed in principle to use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a6e037390c515050b2b19a5679d9362
https://doi.org/10.1007/978-3-030-75549-2_15
https://doi.org/10.1007/978-3-030-75549-2_15
Publikováno v:
Computational Diffusion MRI ISBN: 9783030876142
CDMRI@MICCAI
CDMRI@MICCAI
We present a tissue classifier for Magnetic Resonance Diffusion Weighted Imaging (DWI) data trained from a single subject with a single b-value. The classifier is based on a Riemannian Deep Learning framework for extracting features with rotational i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5bc89ff97b5939e7140a1470b912052c
https://doi.org/10.1007/978-3-030-87615-9_11
https://doi.org/10.1007/978-3-030-87615-9_11
Publikováno v:
Hu, X, Lauze, F, Pedersen, K S & Melou, J 2021, Absolute and Relative Pose Estimation in Refractive Multi View . in Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) . IEEE, pp. 2569-2578, 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 11/10/2021 . https://doi.org/10.1109/ICCVW54120.2021.00290
This paper investigates absolute and relative pose estimation under refraction, which are essential problems for refractive structure from motion. We first present an absolute pose estimation algorithm by leveraging an efficient iterative refinement.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51bd1d8d9c8c9c98297938eceb60b311
https://curis.ku.dk/portal/da/publications/absolute-and-relative-pose-estimation-in-refractive-multi-view(2cf66bac-0937-4a95-8073-d537510db417).html
https://curis.ku.dk/portal/da/publications/absolute-and-relative-pose-estimation-in-refractive-multi-view(2cf66bac-0937-4a95-8073-d537510db417).html
Publikováno v:
International Conference on 3D Vision (3DV 2020)
International Conference on 3D Vision (3DV 2020), Nov 2020, Fukuoka (on line), Japan. pp.384-393, ⟨10.1109/3DV50981.2020.00048⟩
3DV
International Conference on 3D Vision (3DV 2020), Nov 2020, Fukuoka (on line), Japan. pp.384-393, ⟨10.1109/3DV50981.2020.00048⟩
3DV
International audience; In this article we show how to extend the multi-view stereo technique when the object to be reconstructed is inside a transparent-but refractive-material, which causes distortions in the images. We provide a theoretical formul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc36b811e76c9fc1b0c3d84006387240
https://hal.archives-ouvertes.fr/hal-02964852/document
https://hal.archives-ouvertes.fr/hal-02964852/document
Autor:
Jean-François Aujol, Jean-Denis Durou, Arthur Renaudeau, François Lauze, Travis Seng, Fabien Pierre, Axel Carlier
Publikováno v:
ICPR 2020-25th International Conference on Pattern Recognition
ICPR 2020-25th International Conference on Pattern Recognition, Sep 2020, Milan / Virtual, Italy
ICPR
ICPR 2020-25th International Conference on Pattern Recognition, Sep 2020, Milan / Virtual, Italy
ICPR
International audience; We propose to detect defects in old movies, as the first step of a larger framework of old movies restoration by inpainting techniques. The specificity of our work is to learn a film restorer's expertise from a pair of sequenc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b14c857805cfbfd80e6ddaceed7ebcfa
https://hal.archives-ouvertes.fr/hal-02965296/file/ARTHUR_ICPR_2020.pdf
https://hal.archives-ouvertes.fr/hal-02965296/file/ARTHUR_ICPR_2020.pdf
Publikováno v:
SSVM 2019-Seventh International Conference on Scale Space and Variational Methods in Computer Vision
SSVM 2019-Seventh International Conference on Scale Space and Variational Methods in Computer Vision, Jun 2019, Hofgeismar, Germany
Lecture Notes in Computer Science ISBN: 9783030223670
SSVM
SSVM 2019-Seventh International Conference on Scale Space and Variational Methods in Computer Vision, Jun 2019, Hofgeismar, Germany
Lecture Notes in Computer Science ISBN: 9783030223670
SSVM
International audience; We propose a new video inpainting model for movies restoration application. Our model combines structural reconstruction with a diffusion-based method and textural reconstruction with a patch-based method. Both proposed energi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::021c67eef6fc432b278e23df2eee305e
https://hal.archives-ouvertes.fr/hal-02433997/file/ssvm_2019_2.pdf
https://hal.archives-ouvertes.fr/hal-02433997/file/ssvm_2019_2.pdf