{LiDAR} Snowfall Simulation for Robust {3D} Object Detection

Autor: Martin Hahner, Christos Sakaridis, Mario Bijelic, Felix Heide, Fisher Yu, Dengxin Dai, Luc Van Gool

Publikováno v: IEEE/CVF Conference on Computer Vision and Pattern Recognition
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

3D object detection is a central task for applications such as autonomous driving, in which the system needs to localize and classify surrounding traffic agents, even in the presence of adverse weather. In this paper, we address the problem of LiDAR-

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9578afdf4459cbc36e5636f0655e753
https://hdl.handle.net/21.11116/0000-000C-1B50-C21.11116/0000-000C-1B52-A

Learning Accurate and Human-Like Driving using Semantic Maps and Attention

Autor: Simon Hecker, Alexander Liniger, Luc Van Gool, Martin Hahner, Dengxin Dai

Publikováno v: IROS

This paper investigates how end-to-end driving models can be improved to drive more accurately and human-like. To tackle the first issue we exploit semantic and visual maps from HERE Technologies and augment the existing Drive360 dataset with such. T

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9b3494e7931804954adacac1c6db309
http://arxiv.org/abs/2007.07218

Semantic Understanding of Foggy Scenes with Purely Synthetic Data

Autor: Christos Sakaridis, Jan-Nico Zaech, Dengxin Dai, Luc Van Gool, Martin Hahner

Publikováno v: 2019 IEEE Intelligent Transportation Systems Conference (ITSC)

This work addresses the problem of semantic scene understanding under foggy road conditions. Although marked progress has been made in semantic scene understanding over the recent years, it is mainly concentrated on clear weather outdoor scenes. Exte

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a01ccc9fb7cb56d9c35302621e173cd
https://lirias.kuleuven.be/handle/123456789/670416