Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Julien Rabin"'
Autor:
Edouard Oyallon, Julien Rabin
Publikováno v:
Image Processing On Line, Vol 5, Pp 176-218 (2015)
The SURF method (Speeded Up Robust Features) is a fast and robust algorithm for local, similarity invariant representation and comparison of images. Similarly to many other local descriptor-based approaches, interest points of a given image are defin
Externí odkaz:
https://doaj.org/article/2e6a3bc16d7c483dbd40c6099a76b5f9
Publikováno v:
Image Processing On Line, Vol 4, Pp 276-299 (2014)
This contribution deals with the Heeger-Bergen pyramid-based texture analysis/synthesis algorithm. It brings a detailed explanation of the original algorithm tested on many characteristic examples. Our analysis reproduces the original results, but al
Externí odkaz:
https://doaj.org/article/a049950f05b442d88eef96283742b605
Publikováno v:
Journal of Mathematical Imaging and Vision. 65:1-3
Publikováno v:
2022 IEEE International Conference on Image Processing (ICIP).
Publikováno v:
2022 IEEE International Conference on Image Processing (ICIP).
Publikováno v:
2022 IEEE International Conference on Image Processing (ICIP).
Publikováno v:
Computer Graphics Forum
Computer Graphics Forum, Wiley, In press, ⟨10.1111/cgf.13889⟩
Computer Graphics Forum, Wiley, In press, ⟨10.1111/cgf.13889⟩
International audience; This paper describes a novel approach for on demand volumetric texture synthesis based on a deep learning framework that allows for the generation of high quality 3D data at interactive rates. Based on a few example images of
Publikováno v:
Scale Space and Variational Methods in Computer Vision
Scale Space and Variational Methods in Computer Vision, May 2021, Cabourg, France. pp.269--280
Lecture Notes in Computer Science ISBN: 9783030755485
SSVM
Scale Space and Variational Methods in Computer Vision, May 2021, Cabourg, France. pp.269--280
Lecture Notes in Computer Science ISBN: 9783030755485
SSVM
International audience; In this paper, we propose a framework to train a generative model for texture image synthesis from a single example. To do so, we exploit the local representation of images via the space of patches, that is, square sub-images
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2082b3bf5915cd3b9450647855243b87
https://hal.archives-ouvertes.fr/hal-02824076v2/file/texgan_preprint.pdf
https://hal.archives-ouvertes.fr/hal-02824076v2/file/texgan_preprint.pdf
Publikováno v:
Scale Space and Variational Methods in Computer Vision
Scale Space and Variational Methods in Computer Vision, May 2021, Cabourg, France
Lecture Notes in Computer Science ISBN: 9783030755485
SSVM
Scale Space and Variational Methods in Computer Vision, May 2021, Cabourg, France
Lecture Notes in Computer Science ISBN: 9783030755485
SSVM
This paper is devoted to signal processing on point-clouds by means of neural networks. Nowadays, state-of-the-art in image processing and computer vision is mostly based on training deep convolutional neural networks on large datasets. While it is a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63110f7518914acae0eafe8b5b553288
https://hal.archives-ouvertes.fr/hal-03249876
https://hal.archives-ouvertes.fr/hal-03249876
Publikováno v:
ICPR 2020, International Association of Pattern Recognition
ICPR 2020, International Association of Pattern Recognition, IAPR, Jan 2021, Milan, Italy
ICPR
ICPR 2020, International Association of Pattern Recognition, IAPR, Jan 2021, Milan, Italy
ICPR
this work has been also presented in SPML19, ICML Workshop on Security and Privacy of Machine Learning (2019-06-14), Long Beach, California, USA; International audience; With the widespread application of deep networks in industry, membership inferen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a42e10becb2e821c0f3c2c49f6e16ea1
https://hal.archives-ouvertes.fr/hal-02367948
https://hal.archives-ouvertes.fr/hal-02367948