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Claudine Badue

4 accepted papers

2021

Keep Your Eyes on the Lane: Real-Time Attention-Guided Lane Detection

Lucas Tabelini, Rodrigo Berriel, Thiago M. Paixao, Claudine Badue, Alberto F. De Souza, Thiago Oliveira-Santos
CVPR 2021poster

Modern lane detection methods have achieved remarkable performances in complex real-world scenarios, but many have issues maintaining real-time efficiency, which is important for autonomous vehicles. In this work, we propose LaneATT: an anchor-based deep lane detection model, which, akin to other ge…

Cited by 482PDF ↗code ↗Scholar ↗
2020

Fast(er) Reconstruction of Shredded Text Documents via Self-Supervised Deep Asymmetric Metric Learning

Thiago M. Paixao, Rodrigo F. Berriel, Maria C. S. Boeres, Alessandro L. Koerich, Claudine Badue, Alberto F. De Souza +1
CVPR 2020poster

The reconstruction of shredded documents consists in arranging the pieces of paper (shreds) in order to reassemble the original aspect of such documents. This task is particularly relevant for supporting forensic investigation as documents may contain criminal evidence. As an alternative to the labo…

Cited by 13PDF ↗code ↗Scholar ↗
2017

A Model-Predictive Motion Planner for the IARA autonomous car

Vinicius Cardoso, Josias Oliveira, Thomas Teixeira, Claudine Badue, Filipe Mutz, Thiago Oliveira-Santos +2
ICRA 2017poster

We present the Model-Predictive Motion Planner (MPMP) of the Intelligent Autonomous Robotic Automobile (IARA). IARA is a fully autonomous car that uses a path planner to compute a path from its current position to the desired destination. Using this path, the current position, a goal in the path and…

Cited by 50Source ↗Scholar ↗
2015

Image-based mapping, global localization and position tracking using VG-RAM weightless neural networks

Lauro J. Lyrio, Thiago Oliveira-Santos, Claudine Badue, Alberto Ferreira De Souza
ICRA 2015poster

Humans can easily memorize images of places and labels (road names, addresses, etc.) associated with them, as well as trajectories defined by sequences of images and corresponding positions. Later, they are able to remember places' labels and relative positions when seeing the same images again. In…

Cited by 21Source ↗Scholar ↗