1 code implementation • 28 Jun 2023 • Jingwen Wang, Juan Tarrio, Lourdes Agapito, Pablo F. Alcantarilla, Alexander Vakhitov
We present a new methodology for real-time semantic mapping from RGB-D sequences that combines a 2D neural network and a 3D network based on a SLAM system with 3D occupancy mapping.
no code implementations • 7 Oct 2021 • Frederik Warburg, Daniel Hernandez-Juarez, Juan Tarrio, Alexander Vakhitov, Ujwal Bonde, Pablo F. Alcantarilla
Active stereo systems are used in many robotic applications that require 3D information.
no code implementations • 18 Feb 2020 • Ujwal Bonde, Pablo F. Alcantarilla, Stefan Leutenegger
Our approach is distinct from previous works in panoptic segmentation that rely on a combination of a semantic segmentation network with a computationally costly instance segmentation network based on bounding box proposals, such as Mask R-CNN, to guide the prediction of instance labels using a Mixture-of-Expert (MoE) approach.
no code implementations • Autonomous Robots 2018 • Pablo F. Alcantarilla, Simon Stent, Germán Ros, Roberto Arroyo, Riccardo Gherardi
We propose a system for performing structural change detection in street-view videos captured by a vehicle-mounted monocular camera over time.
no code implementations • 27 Jul 2016 • Zhaoyang Lv, Chris Beall, Pablo F. Alcantarilla, Fuxin Li, Zsolt Kira, Frank Dellaert
We propose a continuous optimization method for solving dense 3D scene flow problems from stereo imagery.
no code implementations • 1 Jul 2016 • Pablo F. Alcantarilla, Oliver J. Woodford
Feature-based visual structure and motion reconstruction pipelines, common in visual odometry and large-scale reconstruction from photos, use the location of corresponding features in different images to determine the 3D structure of the scene, as well as the camera parameters associated with each image.
no code implementations • 6 Apr 2016 • German Ros, Simon Stent, Pablo F. Alcantarilla, Tomoki Watanabe
In this work we investigate the problem of road scene semantic segmentation using Deconvolutional Networks (DNs).