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Alberto F. De Souza

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 ↗
2016

A Dataset for Improved RGBD-Based Object Detection and Pose Estimation for Warehouse Pick-and-Place

Colin Rennie, Rahul Shome, Kostas E. Bekris, Alberto F. De Souza
RA-L 2016

An important logistics application of robotics involves manipulators that pick-and-place objects placed in warehouse shelves. A critical aspect of this task corresponds to detecting the pose of a known object in the shelf using visual data. Solving this problem can be assisted by the use of an RGBD

Cited by 217Source ↗Scholar ↗