Search Results for author: Antonio M. López

Found 15 papers, 7 papers with code

Co-training for Deep Object Detection: Comparing Single-modal and Multi-modal Approaches

no code implementations23 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.

Depth Estimation object-detection +1

Intention Recognition of Pedestrians and Cyclists by 2D Pose Estimation

1 code implementation9 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.

Autonomous Vehicles Intent Detection +1

Multimodal End-to-End Autonomous Driving

no code implementations7 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.

Autonomous Driving Imitation Learning +3

On Offline Evaluation of Vision-based Driving Models

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.

Autonomous Driving

Is the Pedestrian going to Cross? Answering by 2D Pose Estimation

no code implementations15 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.

Pedestrian Detection Pose Estimation

Training a Binary Weight Object Detector by Knowledge Transfer for Autonomous Driving

no code implementations17 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.

Autonomous Driving object-detection +2

Slanted Stixels: Representing San Francisco's Steepest Streets

1 code implementation17 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.

Road Detection via On--line Label Transfer

no code implementations10 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.

Pedestrian Detection Video Alignment

Spatiotemporal Stacked Sequential Learning for Pedestrian Detection

no code implementations14 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.

Pedestrian Detection

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