Jacinto C. Nascimento — accepted AI-conference papers

2020

3DRegNet: A Deep Neural Network for 3D Point Registration

G. Dias Pais, Srikumar Ramalingam, Venu Madhav Govindu, Jacinto C. Nascimento, Rama Chellappa, Pedro Miraldo

CVPR 2020poster

We present 3DRegNet, a novel deep learning architecture for the registration of 3D scans. Given a set of 3D point correspondences, we build a deep neural network to address the following two challenges: (i) classification of the point correspondences into inliers/outliers, and (ii) regression of the…

Cited by 275 PDF ↗code ↗Scholar ↗

2019

Multiple Agents Representation Using Motion Fields

Catarina Barata, Jacinto C. Nascimento, Jorge S. Marques

ICASSP 2019accepted

Providing reliable descriptions of the agents in a video scene is an essential task in many applications, such as surveillance. However, most works focus solely on the characterization of pedestrians, which is not sufficient to describe complex scenes, where a variety of vehicles (e.g., bikes and ca…

Cited by 0 Source ↗Scholar ↗

2019

OmniDRL: Robust Pedestrian Detection using Deep Reinforcement Learning on Omnidirectional Cameras

G. Dias Pais, Tiago J. Dias, Jacinto C. Nascimento, Pedro Miraldo

ICRA 2019poster

Pedestrian detection is one of the most explored topics in computer vision and robotics. The use of deep learning methods allowed the development of new and highly competitive algorithms. Deep Reinforcement Learning has proved to be within the state-of-the-art in terms of both detection in perspecti…

Cited by 12 Source ↗Scholar ↗