no code implementations • 18 Oct 2021 • Gustavo Sutter P. Carvalho, Diogo C. Luvizon, Antonio Joia Neto, Andre G. C. Pacheco, Otavio A. B. Penatti
Although our method does not require stereo data for supervision, it reaches results on stereo datasets comparable to the state of the art in a zero-shot scenario.
no code implementations • 26 Nov 2020 • Diogo C. Luvizon, Gustavo Sutter P. Carvalho, Andreza A. dos Santos, Jhonatas S. Conceicao, Jose L. Flores-Campana, Luis G. L. Decker, Marcos R. Souza, Helio Pedrini, Antonio Joia, Otavio A. B. Penatti
We present a new lightweight CNN for depth estimation, which is learned by knowledge distillation from a larger network.
no code implementations • 6 Oct 2020 • Allan Pinto, Manuel A. Córdova, Luis G. L. Decker, Jose L. Flores-Campana, Marcos R. Souza, Andreza A. dos Santos, Jhonatas S. Conceição, Henrique F. Gagliardi, Diogo C. Luvizon, Ricardo da S. Torres, Helio Pedrini
Stereo vision is a growing topic in computer vision due to the innumerable opportunities and applications this technology offers for the development of modern solutions, such as virtual and augmented reality applications.
1 code implementation • 15 Dec 2019 • Diogo C. Luvizon, Hedi Tabia, David Picard
In this work, we propose a multi-task framework for jointly estimating 2D or 3D human poses from monocular color images and classifying human actions from video sequences.
Ranked #141 on 3D Human Pose Estimation on Human3.6M
1 code implementation • 21 Nov 2019 • Diogo C. Luvizon, Hedi Tabia, David Picard
3D human pose estimation is frequently seen as the task of estimating 3D poses relative to the root body joint.
Ranked #68 on 3D Human Pose Estimation on Human3.6M
2 code implementations • CVPR 2018 • Diogo C. Luvizon, David Picard, Hedi Tabia
Action recognition and human pose estimation are closely related but both problems are generally handled as distinct tasks in the literature.
Ranked #1 on Action Recognition In Videos on NTU RGB+D
1 code implementation • 6 Oct 2017 • Diogo C. Luvizon, Hedi Tabia, David Picard
In this paper, we propose an end-to-end trainable regression approach for human pose estimation from still images.
Ranked #11 on Pose Estimation on Leeds Sports Poses