no code implementations • 15 May 2024 • Guo Yachan, Xiao Yi, Xue Danna, Jose Luis Gomez Zurita, Antonio M. López
Unsupervised Domain Adaptation (UDA) aims to transfer knowledge learned from a labeled source domain to an unlabeled target domain.
no code implementations • 30 Apr 2024 • Diego Porres, Yi Xiao, Gabriel Villalonga, Alexandre Levy, Antonio M. López
Vision-based end-to-end driving models trained by imitation learning can lead to affordable solutions for autonomous driving.
no code implementations • 19 Dec 2023 • Jose L. Gómez, Manuel Silva, Antonio Seoane, Agnès Borrás, Mario Noriega, Germán Ros, Jose A. Iglesias-Guitian, Antonio M. López
We introduce UrbanSyn, a photorealistic dataset acquired through semi-procedurally generated synthetic urban driving scenarios.
1 code implementation • 29 Apr 2023 • Maciej Wielgosz, Antonio M. López, Muhammad Naveed Riaz
We present a sample dataset featuring pedestrians generated using the ARCANE framework, a new framework for generating datasets in CARLA (0. 9. 13).
1 code implementation • 31 May 2022 • Jose L. Gómez, Gabriel Villalonga, Antonio M. López
In this paper, we propose a new co-training procedure for synth-to-real UDA of semantic segmentation models.
no code implementations • 23 Apr 2021 • Jose L. Gómez, Gabriel Villalonga, Antonio M. López
This data labeling bottleneck may be intensified due to domain shifts among image sensors, which could force per-sensor data labeling.
1 code implementation • 22 Mar 2021 • Akhil Gurram, Ahmet Faruk Tuna, Fengyi Shen, Onay Urfalioglu, Antonio M. López
In this paper, we perform monocular depth estimation by virtual-world supervision (MonoDEVS) and real-world SfM self-supervision.
1 code implementation • ICCV 2019 • Hamed H. Aghdam, Abel Gonzalez-Garcia, Joost Van de Weijer, Antonio M. López
In this paper, we propose a method to perform active learning of object detectors based on convolutional neural networks.
1 code implementation • 9 Oct 2019 • Zhijie Fang, Antonio M. López
In this paper, we show how the same methodology can be used for recognizing pedestrians and cyclists' intentions.
no code implementations • 7 Jun 2019 • Yi Xiao, Felipe Codevilla, Akhil Gurram, Onay Urfalioglu, Antonio M. López
On the other hand, we find end-to-end driving approaches that try to learn a direct mapping from input raw sensor data to vehicle control signals.
2 code implementations • ICCV 2019 • Felipe Codevilla, Eder Santana, Antonio M. López, Adrien Gaidon
Driving requires reacting to a wide variety of complex environment conditions and agent behaviors.
Ranked #17 on Autonomous Driving on CARLA Leaderboard
1 code implementation • ECCV 2018 • Felipe Codevilla, Antonio M. López, Vladlen Koltun, Alexey Dosovitskiy
We show that the correlation of offline evaluation with driving quality can be significantly improved by selecting an appropriate validation dataset and suitable offline metrics.
no code implementations • 15 Jul 2018 • Zhijie Fang, Antonio M. López
Our recent work suggests that, thanks to nowadays powerful CNNs, image-based 2D pose estimation is a promising cue for determining pedestrian intentions such as crossing the road in the path of the ego-vehicle, stopping before entering the road, and starting to walk or bending towards the road.
no code implementations • 17 Apr 2018 • Jiaolong Xu, Peng Wang, Heng Yang, Antonio M. López
Autonomous driving has harsh requirements of small model size and energy efficiency, in order to enable the embedded system to achieve real-time on-board object detection.
1 code implementation • 17 Jul 2017 • Daniel Hernandez-Juarez, Lukas Schneider, Antonio Espinosa, David Vázquez, Antonio M. López, Uwe Franke, Marc Pollefeys, Juan C. Moure
In this work we present a novel compact scene representation based on Stixels that infers geometric and semantic information.
2 code implementations • 2 Dec 2016 • David Vázquez, Jorge Bernal, F. Javier Sánchez, Gloria Fernández-Esparrach, Antonio M. López, Adriana Romero, Michal Drozdzal, Aaron Courville
Colorectal cancer (CRC) is the third cause of cancer death worldwide.
no code implementations • 5 Nov 2016 • Victor Campmany, Sergio Silva, Antonio Espinosa, Juan Carlos Moure, David Vázquez, Antonio M. López
We propose a real-time pedestrian detection system for the embedded Nvidia Tegra X1 GPU-CPU hybrid platform.
no code implementations • 10 Dec 2014 • José M. Álvarez, Ferran Diego, Joan Serrat, Antonio M. López
The major challenges of road detection are dealing with shadows and lighting variations and the presence of other objects in the scene.
no code implementations • 14 Jul 2014 • Alejandro González, Sebastian Ramos, David Vázquez, Antonio M. López, Jaume Amores
In particular, we propose to use two-stage classifiers which not only rely on the image descriptors required by the base classifiers but also on the response of such base classifiers in a given spatiotemporal neighborhood.