Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous driving
Paper i proceeding, 2023

Existing datasets for autonomous driving (AD) often lack diversity and long-range capabilities, focusing instead on 360° perception and temporal reasoning. To address this gap, we introduce Zenseact Open Dataset (ZOD), a large- scale and diverse multimodal dataset collected over two years in various European countries, covering an area 9×that of existing datasets. ZOD boasts the highest range and resolution sensors among comparable datasets, coupled with detailed keyframe annotations for 2D and 3D objects (up to 245m), road instance/semantic segmentation, traffic sign recognition, and road classification. We believe that this unique combination will facilitate breakthroughs in long-range perception and multi-task learning. The dataset is composed of Frames, Sequences, and Drives, designed to encompass both data diversity and support for spatio-temporal learning, sensor fusion, localization, and mapping. Frames consist of 100k curated camera images with two seconds of other supporting sensor data, while the 1473 Sequences and 29 Drives include the entire sensor suite for 20 seconds and a few minutes, respectively. ZOD is the only large-scale AD dataset released under a permissive license, allowing for both research and commercial use. More information, and an extensive devkit, can be found at zod.zenseact.com.

autonoma fordon

dataset

Autonomous driving

Författare

Mina Alibeigi

William Ljungbergh

Adam Tonderski

Georg Hess

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Adam Lilja

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Carl Lindström

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Daria Motorniuk

Junsheng Fu

Jenny Widahl

Christoffer Petersson

Chalmers, Matematiska vetenskaper, Algebra och geometri

2023 IEEE/CVF International Conference on Computer Vision

2380-7504 (ISSN)

20121-20131
979-8-3503-0718-4 (ISBN)


Paris, France,

Följning av objekt för självkörande fordon med hjälp av djup maskininlärning

Wallenberg AI, Autonomous Systems and Software Program, 2021-08-01 -- 2025-08-01.

Styrkeområden

Transport

Ämneskategorier

Datavetenskap (datalogi)

Datorseende och robotik (autonoma system)

DOI

10.1109/ICCV51070.2023.01846

Relaterade dataset

Zenseact Open Dataset [dataset]

URI: https://zod.zenseact.com/

Mer information

Skapat

2024-04-12