Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Kherroubi, Josselin"'
Even though data annotation is extremely important for interpretability, research and development of artificial intelligence solutions, most research efforts such as active learning or few-shot learning focus on the sample efficiency problem. This pa
Externí odkaz:
http://arxiv.org/abs/2307.01578
Autor:
Saad, Ahmed Ben, Prokopetc, Kristina, Kherroubi, Josselin, Davy, Axel, Courtois, Adrien, Facciolo, Gabriele
Self-supervised representation learning based on Contrastive Learning (CL) has been the subject of much attention in recent years. This is due to the excellent results obtained on a variety of subsequent tasks (in particular classification), without
Externí odkaz:
http://arxiv.org/abs/2211.10177
We tackle the problem of texture inpainting where the input images are textures with missing values along with masks that indicate the zones that should be generated. Many works have been done in image inpainting with the aim to achieve global and lo
Externí odkaz:
http://arxiv.org/abs/1911.02274
Autor:
Saad, Ahmed Ben, Prokopetc, Kristina, Kherroubi, Josselin, Davy, Axel, Courtois, Adrien, Facciolo, Gabriele
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Self-supervised representation learning based on Contrastive Learning (CL) has been the subject of much attention in recent years. This is due to the excellent results obtained on a variety of subsequent tasks (in particular classification), without
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12e0f184219c3d7fa1026d0403c43634
https://doi.org/10.1109/wacv56688.2023.00241
https://doi.org/10.1109/wacv56688.2023.00241
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