Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Rodrigo De Bem"'
Autor:
Wellington Silveira, Andrew Alaniz, Marina Hurtado, Bernardo Castello Da Silva, Rodrigo De Bem
Publikováno v:
2022 35th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f099c5de9d3289e3443a890d89900259
https://doi.org/10.1109/sibgrapi55357.2022.9991748
https://doi.org/10.1109/sibgrapi55357.2022.9991748
Publikováno v:
Anais do XVII Workshop de Visão Computacional (WVC 2021).
Multiple sclerosis is an autoimmune disease that affects the central nervous system, destroying myelin. To detect multiple sclerosis, you need to have MRI scans so you can see the areas where myelin has been damaged. This analysis is complex and cost
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c3b3d57cc9cfdb99308b8f21f9138e96
https://doi.org/10.5753/wvc.2021.18912
https://doi.org/10.5753/wvc.2021.18912
Publikováno v:
SAC
Overexposed and underexposed digital images may occur either by excess or deficiency of lighting during acquisition. These problems are common in uncontrolled environments, specially affecting the visual sensory of autonomous robotic vehicles outdoor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::791da24aff36dbd88c91e463ac8f9670
https://doi.org/10.1145/3412841.3441955
https://doi.org/10.1145/3412841.3441955
Publikováno v:
CVPR
We present in this work the first end-to-end deep learning based method that predicts both 3D hand shape and pose from RGB images in the wild. Our network consists of the concatenation of a deep convolutional encoder, and a fixed model-based decoder.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2331673e41ec96d1c2db8c86edfca45d
https://doi.org/10.1109/cvpr.2019.01110
https://doi.org/10.1109/cvpr.2019.01110
Autor:
Adnane Boukhayma, Philip H. S. Torr, Arnab Ghosh, N. Siddharth, Thalaiyasingam Ajanthan, Rodrigo de Bem
Publikováno v:
WACV
We propose a deep generative model of humans in natural images which keeps 2D pose separated from other latent factors of variation, such as background scene and clothing. In contrast to methods that learn generative models of low-dimensional represe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c016b186af666f6b3f26f3fd6d0ecee
https://doi.org/10.1109/wacv.2019.00159
https://doi.org/10.1109/wacv.2019.00159
Autor:
Philip H. S. Torr, Arnab Ghosh, Rodrigo de Bem, Thalaiyasingam Ajanthan, N. Siddharth, Ondrej Miksik
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030110116
ECCV Workshops (2)
ECCV Workshops (2)
Deep generative modelling for human body analysis is an emerging problem with many interesting applications. However, the latent space learned by such models is typically not interpretable, resulting in less flexible models. In this work, we adopt a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a59131b5e4455e067d406811d82c58e1
https://doi.org/10.1007/978-3-030-11012-3_38
https://doi.org/10.1007/978-3-030-11012-3_38
Autor:
Adnane Boukhayma, N. Siddharth, Philip H. S. Torr, Ondrej Miksik, Arnab Ghosh, Thalaiyasingam Ajanthan, Rodrigo de Bem
Publikováno v:
de Bem, R, Ghosh, A, Ajanthan, T, Miksik, O, Boukhayma, A, Siddharth, N & Torr, P 2020, ' DGPose: Deep Generative Models for Human Body Analysis ', International Journal of Computer Vision, vol. 128, no. 5, pp. 1537-1563 . https://doi.org/10.1007/s11263-020-01306-1
Deep generative modelling for human body analysis is an emerging problem with many interesting applications. However, the latent space learned by such approaches is typically not interpretable, resulting in less flexibility. In this work, we present
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a58cbc18963bb2ec8536a4d6944f92a1
http://arxiv.org/abs/1804.06364
http://arxiv.org/abs/1804.06364
Publikováno v:
Journal of Communication and Information Systems. 30:100-108
Markerless human motion tracking can be employed in many applications such as automatic surveillance, motion capture, human-machine interface and activity recognition. This problem has been extensively studied in the computer vision research communit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7363675f16d9b5d12517c0faf2041050
https://doi.org/10.14209/jcis.2015.12
https://doi.org/10.14209/jcis.2015.12
Publikováno v:
PETRA
Sleep disorders affect approximately 30% of the adult population, due to this fact, it is considered an important public health issue. Some medical conditions are correlated with sleep disturbances, including: obesity, diabetes, cardiovascular diseas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96129053e622e2634135d5aea9ce12b6
https://doi.org/10.1145/2769493.2769563
https://doi.org/10.1145/2769493.2769563
Publikováno v:
ICRA
Most existing motion tracking methods works in specific predefined situations and requires large amount of a priori information about the target objects, such as, their shapes, appearances, kinematic structures, possible moves and physically valid po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::86f1658ec633072a285d71191d61de16
https://doi.org/10.1109/icra.2013.6630786
https://doi.org/10.1109/icra.2013.6630786