1 code implementation • 6 Jun 2021 • Jean Pablo Vieira de Mello, Thiago M. Paixão, Rodrigo Berriel, Mauricio Reyes, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos
The analysis of Magnetic Resonance Imaging (MRI) sequences enables clinical professionals to monitor the progression of a brain tumor.
1 code implementation • 21 Jan 2021 • Jacson Rodrigues Correia-Silva, Rodrigo F. Berriel, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos
In a preliminary work, we presented a simple, yet powerful, method to copy black-box models by querying them with natural random images.
1 code implementation • 7 Nov 2020 • Jean Pablo Vieira de Mello, Lucas Tabelini, Rodrigo F. Berriel, Thiago M. Paixão, Alberto F. de Souza, Claudine Badue, Nicu Sebe, Thiago Oliveira-Santos
By providing real image samples with traffic context to the network, the model learns to detect and classify elements of interest, such as pedestrians, traffic signs, and traffic lights.
2 code implementations • CVPR 2021 • Lucas Tabelini, Rodrigo Berriel, Thiago M. Paixão, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos
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.
Ranked #6 on Lane Detection on LLAMAS
no code implementations • 19 Sep 2020 • Filipe Mutz, Thiago Oliveira-Santos, Avelino Forechi, Karin S. Komati, Claudine Badue, Felipe M. G. França, Alberto F. de Souza
In this work, we provide data for such analysis by comparing the accuracy of a particle filter localization when using occupancy, reflectivity, color, or semantic grid maps.
no code implementations • 30 Jul 2020 • Lucas Tabelini, Rodrigo Berriel, Thiago M. Paixão, Alberto F. de Souza, Claudine Badue, Nicu Sebe, Thiago Oliveira-Santos
The method does not aim at overcoming the training with real data, but to be a compatible alternative when the real data is not available.
1 code implementation • 1 Jul 2020 • Thiago M. Paixão, Rodrigo F. Berriel, Maria C. S. Boeres, Alessandro L. Koerich, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos
The solution presented in this work extends our previous deep learning method for single-page reconstruction to a more realistic/complex scenario: the reconstruction of several mixed shredded documents at once.
1 code implementation • arXiv 2020 • Lucas Tabelini, Rodrigo Berriel, Thiago M. Paixão, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos
One of the main factors that contributed to the large advances in autonomous driving is the advent of deep learning.
Ranked #9 on Lane Detection on LLAMAS
1 code implementation • 23 Mar 2020 • Thiago M. Paixão, Rodrigo F. Berriel, Maria C. S. Boeres, Alessando L. Koerich, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos
The reconstruction of shredded documents consists in arranging the pieces of paper (shreds) in order to reassemble the original aspect of such documents.
no code implementations • 2 Oct 2019 • Pedro Azevedo, Sabrina S. Panceri, Rânik Guidolini, Vinicius B. Cardoso, Claudine Badue, Thiago Oliveira-Santos, Alberto F. de Souza
We propose a bio-inspired foveated technique to detect cars in a long range camera view using a deep convolutional neural network (DCNN) for the IARA self-driving car.
1 code implementation • 23 Jul 2019 • Lucas Tabelini Torres, Thiago M. Paixão, Rodrigo F. Berriel, Alberto F. de Souza, Claudine Badue, Nicu Sebe, Thiago Oliveira-Santos
Deep learning has been successfully applied to several problems related to autonomous driving.
1 code implementation • 19 Jul 2019 • Vinicius F. Arruda, Thiago M. Paixão, Rodrigo F. Berriel, Alberto F. De Souza, Claudine Badue, Nicu Sebe, Thiago Oliveira-Santos
In this work, a method for training a car detection system with annotated data from a source domain (day images) without requiring the image annotations of the target domain (night images) is presented.
1 code implementation • 4 Jun 2019 • Lucas C. Possatti, Rânik Guidolini, Vinicius B. Cardoso, Rodrigo F. Berriel, Thiago M. Paixão, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos
However, none of them combine the power of the deep learning-based detectors with prior maps to recognize the state of the relevant traffic lights.
no code implementations • 4 Oct 2018 • Thomas Teixeira, Filipe Mutz, Karin Satie Komati, Lucas Veronese, Vinicius B. Cardoso, Claudine Badue, Thiago Oliveira-Santos, Alberto F. de Souza
The objective of map decay is to correct invalid occupancy probabilities of map cells that are unobservable by sensors.
no code implementations • 15 Jun 2018 • Rodrigo F. Berriel, Edilson de Aguiar, Alberto F. de Souza, Thiago Oliveira-Santos
The dataset was manually annotated and made publicly available to enable evaluation of several events that are of interest for the research community (i. e., lane estimation, change, and centering; road markings; intersections; LMTs; crosswalks and adjacent lanes).
1 code implementation • 14 Jun 2018 • Jacson Rodrigues Correia-Silva, Rodrigo F. Berriel, Claudine Badue, Alberto F. de Souza, Thiago Oliveira-Santos
The copy is two-fold: i) the target network is queried with random data and its predictions are used to create a fake dataset with the knowledge of the network; and ii) a copycat network is trained with the fake dataset and should be able to achieve similar performance as the target network.
no code implementations • 30 May 2018 • Rodrigo F. Berriel, Franco Schmidt Rossi, Alberto F. de Souza, Thiago Oliveira-Santos
Many crosswalk classification, detection and localization systems have been proposed in the literature over the years.
1 code implementation • 8 May 2018 • Avelino Forechi, Thiago Oliveira-Santos, Claudine Badue, Alberto F. de Souza
One of them is known as place recognition, which associates images of places with their corresponding positions.
no code implementations • 27 Apr 2018 • Raphael V. Carneiro, Rafael C. Nascimento, Rânik Guidolini, Vinicius B. Cardoso, Thiago Oliveira-Santos, Claudine Badue, Alberto F. de Souza
We propose the use of deep neural networks (DNN) for solving the problem of inferring the position and relevant properties of lanes of urban roads with poor or absent horizontal signalization, in order to allow the operation of autonomous cars in such situations.
1 code implementation • 28 Jun 2017 • Rodrigo F. Berriel, Andre Teixeira Lopes, Alberto F. de Souza, Thiago Oliveira-Santos
In this letter, crowdsourcing systems are exploited in order to enable the automatic acquisition and annotation of a large-scale satellite imagery database for crosswalks related tasks.
no code implementations • 3 Sep 2015 • Colin Rennie, Rahul Shome, Kostas E. Bekris, Alberto F. de Souza
This paper provides a new rich data set for advancing the state-of-the-art in RGBD- based 3D object pose estimation, which is focused on the challenges that arise when solving warehouse pick- and-place tasks.