Folgen
Rodrigo de Bem
Rodrigo de Bem
Department of Engineering Science, University of Oxford
Bestätigte E-Mail-Adresse bei robots.ox.ac.uk - Startseite
Titel
Zitiert von
Zitiert von
Jahr
3d hand shape and pose from images in the wild
A Boukhayma, R de Bem, PHS Torr
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
4012019
Analyzing and exploring feature detectors in images
P Drews, R de Bem, A de Melo
9th IEEE International Conference on Industrial Informatics (INDIN), 305-310, 2011
282011
A conditional deep generative model of people in natural images
R de Bem, A Ghosh, A Boukhayma, T Ajanthan, N Siddharth, P Torr
IEEE Winter Conference on Applications of Computer Vision (WACV), 1449-1458, 2019
232019
Deep fully-connected part-based models for human pose estimation
R de Bem, A Arnab, S Golodetz, M Sapienza, P Torr
Asian Conference on Machine Learning (ACML), 327-342, 2018
192018
A semi-supervised deep generative model for human body analysis
R de Bem, A Ghosh, T Ajanthan, O Miksik, N Siddharth, P Torr
European Conference on Computer Vision (ECCV) Workshops, 2018
172018
C-NLPCA: Extracting Non-Linear Principal Components of Image Datasets
SSC Botelho, R de Bem, ÍL Almeida, MM Mata
XII Simpósio Brasileiro de Sensoriamento Remoto (SBSR), 3495-3502, 2005
172005
DGPose: Deep Generative Models for Human Body Analysis.
R de Bem, A Ghosh, T Ajanthan, O Miksik, A Boukhayma, N Siddharth, ...
Int. J. Comput. Vis. 128 (5), 1537-1563, 2020
162020
Hardware and Software Infrastructure to Image Acquisition using Multiple Cameras
D Thiel, M Goulart, S Botelho, R de Bem
XXVI Conference on Graphics, Patterns, and Images (SIBGRAPI) - Workshop of …, 2013
7*2013
Applying neural networks to study the mesoscale variability of oceanic boundary currents
SSC Botelho, MM Mata, R de Bem, I Almeida
14th Intl Symposium on Methodologies for Intelligent Systems (ISMIS), 684-688, 2003
72003
Utilizando visão computacional para reconstrução probabilística 3D e rastreamento de movimento
GM Simas, GP Fickel, L Novelo, R de Bem, SSC Botelho
VETOR-Revista de Ciências Exatas e Engenharias 17 (2), 59-77, 2007
52007
A model-free approach for object tracking in sequences of images
R de Bem
Master's thesis, University of Sao Paulo, Brazil, 2007
5*2007
SynLibras: A Disentangled Deep Generative Model for Brazilian Sign Language Synthesis
W Silveira, A Alaniz, M Hurtado, BC Da Silva, R De Bem
2022 35th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) 1 …, 2022
42022
3D motion tracking based on probabilistic volumetric reconstruction and optical flow
GM Simas, GP Fickel, L Novelo, R de Bem, SSC Botelho
23rd Conference on Graphics, Patterns and Images (SIBGRAPI), 279-286, 2010
42010
Fast Spatial-Temporal Transformer Network
RM Escher, RA de Bem, PLJ Drews
2021 34th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), 65-72, 2021
32021
Rastreamento visual de múltiplos objetos utilizando uma abordagem livre de modelo
R de Bem, AHR Costa
XVI Congresso Brasileiro de Automática (CBA), 2760-2765, 2006
32006
Performance Evaluation of BRISK Algorithm on Mobile Devices.
A Gularte, C Thomasi, R de Bem, DF Adamatti
8th Intl Conference on Computer Vision Theory and Applications (VISAPP), 5-11, 2013
22013
The Role of Aggregation Functions on Transformers and ViTs Self-Attention for Classification
J Sartori, R de Bem, G Dimuro, G Lucca
2023 36th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI …, 2023
12023
Soybean Weeds Segmentation Using VT-Net: A Convolutional-Transformer Model
L Silva, P Drews, R de Bem
2023 36th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI …, 2023
12023
A 3d motion tracking method based on nonparametric belief propagation
G Simas, R de Bem, S Botelho
IEEE International Conference on Robotics and Automation (ICRA), 1616-1622, 2013
12013
3D Representation Models Construction through a Volume Geometric Decomposition Method
G Simas, R de Bem, S Botelho
8th Intl Conference on Computer Vision Theory and Applications (VISAPP), 274-279, 2013
12013
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20