Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Bruno Lecouat"'
Autor:
Yasin Yazici, Bruno Lecouat, Kim Hui Yap, Stefan Winkler, Georgios Piliouras, Vijay Chandrasekhar, Chuan-Sheng Foo
Publikováno v:
2022 IEEE International Conference on Image Processing (ICIP).
Publikováno v:
European Conference on Computer Vision (ECCV) 2020
ECCV 2020-European Conference on Computer Vision
ECCV 2020-European Conference on Computer Vision, Aug 2020, Glasgow / Virtual, United Kingdom. pp.238-254, ⟨10.1007/978-3-030-58542-6_15⟩
Computer Vision – ECCV 2020 ISBN: 9783030585419
ECCV (22)
Computer Vision – ECCV 2020-16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXII
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Computer Vision – ECCV 2020
ECCV 2020-European Conference on Computer Vision
ECCV 2020-European Conference on Computer Vision, Aug 2020, Glasgow / Virtual, United Kingdom. pp.238-254, ⟨10.1007/978-3-030-58542-6_15⟩
Computer Vision – ECCV 2020 ISBN: 9783030585419
ECCV (22)
Computer Vision – ECCV 2020-16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXII
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Computer Vision – ECCV 2020
Non-local self-similarity and sparsity principles have proven to be powerful priors for natural image modeling. We propose a novel differentiable relaxation of joint sparsity that exploits both principles and leads to a general framework for image re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a242267d7c1b14f43a57eeea86e137ac
https://hal.inria.fr/hal-02414291v3/file/paper.pdf
https://hal.inria.fr/hal-02414291v3/file/paper.pdf
Autor:
Magauiya Zhussip, Julien Mairal, Ziwei Luo, Christian Micheloni, Haoqiang Fan, Sanghyeok Son, Jean Ponce, Rao Muhammad, Ziluan Liu, Kazutoshi Akita, Xuan Mo, Umer Youliang Yan, Pavel Ostyakov, Youwei Li, Martin Danelljan, Norimichi Ukita, Bruno Lecouat, Lei Yu, Xueyi Zou, Goutam Bhat, Radu Timofte, Shuaicheng Liu, Dae-Shik Kim, Jian Sun, Lanpeng Jia, Wooyeong Cho, Takahiro Maeda, Takeru Oba
Publikováno v:
CVPR Workshops
This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times higher resolution. The challenge contained two tracks; Track 1 evaluating
Publikováno v:
ICDM
Anomaly detection is a significant and hence well-studied problem. However, developing effective anomaly detection methods for complex and high-dimensional data remains a challenge. As Generative Adversarial Networks (GANs) are able to model the comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cfc01bae793e17a8976e2bc1f969ca80
http://arxiv.org/abs/1812.02288
http://arxiv.org/abs/1812.02288
We introduce a general framework for designing and learning neural networks whose forward passes can be interpreted as solving convex optimization problems, and whose architectures are derived from an optimization algorithm. We focus on non-cooperati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ff0aa6fb4a213cabb714764f8477b44c
https://hal.archives-ouvertes.fr/hal-02881924
https://hal.archives-ouvertes.fr/hal-02881924