logo
logo
Sign in

Best Open-Source Autonomous Driving Datasets

avatar
Alexandra Nguyen
Best Open-Source Autonomous Driving Datasets

In recent years, more and more companies and research institutions have made their autonomous driving datasets open to the public. However, the best datasets are not always easy to find, and scouring the internet for them takes time.

To help, we at SiaSearch have put together a list of the top 15 open datasets for autonomous driving. The resources below collectively contain millions of data samples, many of which are already annotated. We hope this list provides you with a solid starting point for learning more about the field, or for starting your own autonomous driving project.

Top Open Datasets for Autonomous Driving Projects

1. A2D2 Dataset

The Audi Autonomous Driving Dataset (A2D2) features over 41,000 labeled with 38 features. Around 2.3 TB in total, A2D2 is split by annotation type (i.e. semantic segmentation, 3D bounding box).

2. ApolloScape Dataset

ApolloScape is an evolving research project that aims to foster innovation across all aspects of autonomous driving, from perception to navigation and control. Via their website, users can explore a variety of simulation tools and over 100K street view frames, 80k lidar point cloud and 1000km trajectories for urban traffic.

An example of lanemark segmentation in the ApolloScape dataset

An example of lanemark segmentation in the ApolloScape dataset

3. Argoverse Dataset

The Argoverse dataset includes 3D tracking annotations for 113 scenes and over 324,000 unique vehicle trajectories for motion forecasting.

4. Berkeley DeepDrive Dataset

Also known as BDD 100K, the DeepDrive dataset gives users access to 100,000 annotated videos and 10 tasks to evaluate image recognition algorithms for autonomous driving. The dataset represents more than 1000 hours of driving experience with more than 100 million frames, as well as information on geographic, environmental, and weather diversity.

5. CityScapes Dataset

CityScapes is a large-scale dataset focused on the semantic understanding of urban street scenes in 50 German cities. It features semantic, instance-wise, and dense pixel annotations for 30 classes grouped into 8 categories. The entire dataset includes 5,000 annotated images with fine annotations, and an additional 20,000 annotated images with coarse annotations.

Examples of scenes from the CityScapes dataset - overlayed colors encode semantic classes

Examples of scenes from the CityScapes dataset - overlayed colors encode semantic classes

Want more datasets?

Read the whole list originally published at: https://www.siasearch.io/blog/best-open-source-autonomous-driving-datasets

A proud supporter of the research community, SiaSearch offers enhanced access to popular autonomous driving datasets such as nuScenes and KITTI via our Open Data initiative. In fact, many of the datasets on this list have already been integrated into our platform.

Sign up for a free account to easily query, curate, and transform datasets for autonomous driving: http://public.sia-search.com/

collect
0
avatar
Alexandra Nguyen
guide
Zupyak is the world’s largest content marketing community, with over 400 000 members and 3 million articles. Explore and get your content discovered.
Read more