46 citations · 77 across the 9 of their papers we have counts for
5 papers · 1 filter
CCNeXt: An Effective Self-Supervised Stereo Depth Estimation Approach
Alexandre Lopes, Roberto Souza, Helio Pedrini
Depth Estimation plays a crucial role in recent applications in robotics, autonomous vehicles, and augmented reality. These scenarios commonly operate under constraints imposed by…
Computer Vision Model Compression Techniques for Embedded Systems: A Survey
Alexandre Lopes, Fernando Pereira dos Santos, Diulhio de Oliveira +2
Deep neural networks have consistently represented the state of the art in most computer vision problems. In these scenarios, larger and more complex models have demonstrated super…
P-NOC: adversarial training of CAM generating networks for robust weakly supervised semantic segmentation priors
Lucas David, Helio Pedrini, Zanoni Dias
Weakly Supervised Semantic Segmentation (WSSS) techniques explore individual regularization strategies to refine Class Activation Maps (CAMs). In this work, we first analyze comple…
Global Semantic Descriptors for Zero-Shot Action Recognition
Valter Estevam, Rayson Laroca, Helio Pedrini +1
The success of Zero-shot Action Recognition (ZSAR) methods is intrinsically related to the nature of semantic side information used to transfer knowledge, although this aspect has…
A Survey on RGB-D Datasets
Alexandre Lopes, Roberto Souza, Helio Pedrini
RGB-D data is essential for solving many problems in computer vision. Hundreds of public RGB-D datasets containing various scenes, such as indoor, outdoor, aerial, driving, and med…