Argoverse: 3d tracking and forecasting with rich maps
We present Argoverse, a dataset designed to support autonomous vehicle perception tasks
including 3D tracking and motion forecasting. Argoverse includes sensor data collected by a …
including 3D tracking and motion forecasting. Argoverse includes sensor data collected by a …
nuscenes: A multimodal dataset for autonomous driving
Robust detection and tracking of objects is crucial for the deployment of autonomous vehicle
technology. Image based benchmark datasets have driven development in computer vision …
technology. Image based benchmark datasets have driven development in computer vision …
Wilds: A benchmark of in-the-wild distribution shifts
Distribution shifts—where the training distribution differs from the test distribution—can
substantially degrade the accuracy of machine learning (ML) systems deployed in the wild …
substantially degrade the accuracy of machine learning (ML) systems deployed in the wild …
Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges
Recent advancements in perception for autonomous driving are driven by deep learning. In
order to achieve robust and accurate scene understanding, autonomous vehicles are …
order to achieve robust and accurate scene understanding, autonomous vehicles are …
The apolloscape dataset for autonomous driving
Scene parsing aims to assign a class (semantic) label for each pixel in an image. It is a
comprehensive analysis of an image. Given the rise of autonomous driving, pixel-accurate …
comprehensive analysis of an image. Given the rise of autonomous driving, pixel-accurate …
Deepglobe 2018: A challenge to parse the earth through satellite images
Abstract We present the DeepGlobe 2018 Satellite Image Understanding Challenge, which
includes three public competitions for segmentation, detection, and classification tasks on …
includes three public competitions for segmentation, detection, and classification tasks on …
Neural map prior for autonomous driving
High-definition (HD) semantic maps are a crucial component for autonomous driving on
urban streets. Traditional offline HD maps are created through labor-intensive manual …
urban streets. Traditional offline HD maps are created through labor-intensive manual …