Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Himalaya Jain"'
Publikováno v:
CVPR
Despite the recent progress of generative adversarial networks (GANs) at synthesizing photo-realistic images, producing complex urban scenes remains a challenging problem. Previous works break down scene generation into two consecutive phases: uncond
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7308cabbc94e62872362fad5db8a551b
https://doi.org/10.1109/cvpr46437.2021.00922
https://doi.org/10.1109/cvpr46437.2021.00922
With the rapid advances in generative adversarial networks (GANs), the visual quality of synthesised scenes keeps improving, including for complex urban scenes with applications to automated driving. We address in this work a continual scene generati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71eac08cd9b06d029228a20a78419292
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585884
ECCV (21)
ECCV (21)
Knowledge distillation refers to the process of training a student network to achieve better accuracy by learning from a pre-trained teacher network. Most of the existing knowledge distillation methods direct the student to follow the teacher by matc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59dd5c89214bd41a0df78a57a7435e7f
https://doi.org/10.1007/978-3-030-58589-1_11
https://doi.org/10.1007/978-3-030-58589-1_11
Publikováno v:
ICASSP
ICASSP 2020-45th International Conference on Acoustics, Speech, and Signal Processing
ICASSP 2020-45th International Conference on Acoustics, Speech, and Signal Processing, May 2020, Barcelona, Spain
ICASSP 2020-45th International Conference on Acoustics, Speech, and Signal Processing
ICASSP 2020-45th International Conference on Acoustics, Speech, and Signal Processing, May 2020, Barcelona, Spain
International audience; Current generative networks are increasingly proficient in generating high-resolution realistic images. These generative networks, especially the conditional ones, can potentially become a great tool for providing new image da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7c2116130f35d39e759c558b3d92696
http://arxiv.org/abs/1911.02888
http://arxiv.org/abs/1911.02888
Publikováno v:
ICCV
Unsupervised domain adaptation (UDA) is important for applications where large scale annotation of representative data is challenging. For semantic segmentation in particular, it helps deploy on real "target domain" data models that are trained on an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdbba00c267ae6062ca43be268b91686
https://doi.org/10.1109/iccv.2019.00746
https://doi.org/10.1109/iccv.2019.00746
Publikováno v:
CVPR
Semantic segmentation is a key problem for many computer vision tasks. While approaches based on convolutional neural networks constantly break new records on different benchmarks, generalizing well to diverse testing environments remains a major cha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f99a57229027cafc676432e73672215
http://arxiv.org/abs/1811.12833
http://arxiv.org/abs/1811.12833
Publikováno v:
CVPR 2018-IEEE Conference on Computer Vision and Pattern Recognition
CVPR 2018-IEEE Conference on Computer Vision and Pattern Recognition, Jun 2018, Salt Lake City, United States
CVPR
CVPR 2018-IEEE Conference on Computer Vision and Pattern Recognition, Jun 2018, Salt Lake City, United States
CVPR
International audience; To work at scale, a complete image indexing system comprises two components: An inverted file index to restrict the actual search to only a subset that should contain most of the items relevant to the query; An approximate dis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7ba98a97c0f9764830cb3a6f49c8f30
https://hal.inria.fr/hal-01683385
https://hal.inria.fr/hal-01683385
Publikováno v:
The IEEE International Conference on Computer Vision (ICCV)
The IEEE International Conference on Computer Vision (ICCV), Oct 2017, Venise, Italy. ⟨10.1109/ICCV.2017.96⟩
ICCV
The IEEE International Conference on Computer Vision (ICCV), Oct 2017, Venise, Italy. ⟨10.1109/ICCV.2017.96⟩
ICCV
For large-scale visual search, highly compressed yet meaningful representations of images are essential. Structured vector quantizers based on product quantization and its variants are usually employed to achieve such compression while minimizing the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c8164a1a075a27b5a54655102cf6521
https://hal.inria.fr/hal-01683390
https://hal.inria.fr/hal-01683390
Publikováno v:
Computer Vision – ECCV 2016
14th European Conference on Computer Vision (ECCV)
14th European Conference on Computer Vision (ECCV), Oct 2016, Amsterdam, Netherlands
Computer Vision – ECCV 2016 ISBN: 9783319464770
ECCV (7)
14th European Conference on Computer Vision (ECCV)
14th European Conference on Computer Vision (ECCV), Oct 2016, Amsterdam, Netherlands
Computer Vision – ECCV 2016 ISBN: 9783319464770
ECCV (7)
This paper tackles the task of storing a large collection of vectors, such as visual descriptors, and of searching in it. To this end, we propose to approximate database vectors by constrained sparse coding, where possible atom weights are restricted
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e160ae5b404a0cdab28f72bfe080175c
https://hal.science/hal-01361953/document
https://hal.science/hal-01361953/document