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Antonio M. López
Researcher at Autonomous University of Barcelona
Publications - 215
Citations - 13872
Antonio M. López is an academic researcher from Autonomous University of Barcelona. The author has contributed to research in topics: Pedestrian detection & Object detection. The author has an hindex of 48, co-authored 211 publications receiving 11330 citations. Previous affiliations of Antonio M. López include University of Barcelona & Université de Montréal.
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Proceedings ArticleDOI
The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes
TL;DR: This paper generates a synthetic collection of diverse urban images, named SYNTHIA, with automatically generated class annotations, and conducts experiments with DCNNs that show how the inclusion of SYnTHIA in the training stage significantly improves performance on the semantic segmentation task.
CARLA: An Open Urban Driving Simulator
TL;DR: This work introduces CARLA, an open-source simulator for autonomous driving research, and uses it to study the performance of three approaches to autonomous driving: a classic modular pipeline, an end-to-end model trained via imitation learning, and an end to-end models trained via reinforcement learning.
Journal ArticleDOI
Survey of Pedestrian Detection for Advanced Driver Assistance Systems
TL;DR: This work divides the problem of detecting pedestrians from images into different processing steps, each with attached responsibilities, and separates the different proposed methods with respect to each processing stage, favoring a comparative viewpoint.
Proceedings ArticleDOI
End-to-End Driving Via Conditional Imitation Learning
TL;DR: This work evaluates different architectures for conditional imitation learning in vision-based driving and conducts experiments in realistic three-dimensional simulations of urban driving and on a 1/5 scale robotic truck that is trained to drive in a residential area.
Journal ArticleDOI
Road Detection Based on Illuminant Invariance
Jose M. Alvarez,Antonio M. López +1 more
TL;DR: In this article, a shadow-invariant feature space combined with a model-based classifier is used to detect the free road surface ahead of the ego-vehicle.