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of 18
pro vyhledávání: '"Banani, Mohamed"'
Autor:
Banani, Mohamed El, Raj, Amit, Maninis, Kevis-Kokitsi, Kar, Abhishek, Li, Yuanzhen, Rubinstein, Michael, Sun, Deqing, Guibas, Leonidas, Johnson, Justin, Jampani, Varun
Recent advances in large-scale pretraining have yielded visual foundation models with strong capabilities. Not only can recent models generalize to arbitrary images for their training task, their intermediate representations are useful for other visu
Externí odkaz:
http://arxiv.org/abs/2404.08636
Although an object may appear in numerous contexts, we often describe it in a limited number of ways. Language allows us to abstract away visual variation to represent and communicate concepts. Building on this intuition, we propose an alternative ap
Externí odkaz:
http://arxiv.org/abs/2302.12248
Autor:
Banani, Mohamed El, Rocco, Ignacio, Novotny, David, Vedaldi, Andrea, Neverova, Natalia, Johnson, Justin, Graham, Benjamin
Video provides us with the spatio-temporal consistency needed for visual learning. Recent approaches have utilized this signal to learn correspondence estimation from close-by frame pairs. However, by only relying on close-by frame pairs, those appro
Externí odkaz:
http://arxiv.org/abs/2212.03236
Autor:
Banani, Mohamed El, Johnson, Justin
Geometric feature extraction is a crucial component of point cloud registration pipelines. Recent work has demonstrated how supervised learning can be leveraged to learn better and more compact 3D features. However, those approaches' reliance on grou
Externí odkaz:
http://arxiv.org/abs/2106.00677
Aligning partial views of a scene into a single whole is essential to understanding one's environment and is a key component of numerous robotics tasks such as SLAM and SfM. Recent approaches have proposed end-to-end systems that can outperform tradi
Externí odkaz:
http://arxiv.org/abs/2102.11870
The goal of this paper is to estimate the viewpoint for a novel object. Standard viewpoint estimation approaches generally fail on this task due to their reliance on a 3D model for alignment or large amounts of class-specific training data and their
Externí odkaz:
http://arxiv.org/abs/2006.03586
Autor:
Banani, Mohamed El, Corso, Jason J.
Humans have an unparalleled visual intelligence and can overcome visual ambiguities that machines currently cannot. Recent works have shown that incorporating guidance from humans during inference for monocular viewpoint-estimation can help overcome
Externí odkaz:
http://arxiv.org/abs/1802.01666
Autor:
Tasadduq, Bushra, Wang, Gonghao, El Banani, Mohamed, Mao, Wenbin, Lam, Wilbur, Alexeev, Alexander, Sulchek, Todd
Publikováno v:
In Flow Measurement and Instrumentation October 2015 45:218-224
Autor:
Benlemlih, Amal, Bendahou, Mouhcine, Znati, Kaoutar, Sekkal, Mohamed, Chahbouni, Sanae, Mahmoud, Samia, Banani, Mohamed, Afaf, Amarti
Publikováno v:
Pan African Medical Journal; 2013, Vol. 16, p1-5, 5p
Akademický článek
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