Grid-centric traffic scenario perception for autonomous driving: A comprehensive review
The grid-centric perception is a crucial field for mobile robot perception and navigation.
Nonetheless, the grid-centric perception is less prevalent than object-centric perception as …
Nonetheless, the grid-centric perception is less prevalent than object-centric perception as …
End-to-end autonomous driving: Challenges and frontiers
The autonomous driving community has witnessed a rapid growth in approaches that
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …
Bevformer: learning bird's-eye-view representation from lidar-camera via spatiotemporal transformers
Multi-modality fusion strategy is currently the de-facto most competitive solution for 3D
perception tasks. In this work, we present a new framework termed BEVFormer, which learns …
perception tasks. In this work, we present a new framework termed BEVFormer, which learns …
Maptrv2: An end-to-end framework for online vectorized hd map construction
High-definition (HD) map provides abundant and precise static environmental information of
the driving scene, serving as a fundamental and indispensable component for planning in …
the driving scene, serving as a fundamental and indispensable component for planning in …
Vad: Vectorized scene representation for efficient autonomous driving
Autonomous driving requires a comprehensive understanding of the surrounding
environment for reliable trajectory planning. Previous works rely on dense rasterized scene …
environment for reliable trajectory planning. Previous works rely on dense rasterized scene …
Occworld: Learning a 3d occupancy world model for autonomous driving
Understanding how the 3D scene evolves is vital for making decisions in autonomous
driving. Most existing methods achieve this by predicting the movements of object boxes …
driving. Most existing methods achieve this by predicting the movements of object boxes …
Pivotnet: Vectorized pivot learning for end-to-end hd map construction
Vectorized high-definition map online construction has garnered considerable attention in
the field of autonomous driving research. Most existing approaches model changeable map …
the field of autonomous driving research. Most existing approaches model changeable map …
Genad: Generative end-to-end autonomous driving
Directly producing planning results from raw sensors has been a long-desired solution for
autonomous driving and has attracted increasing attention recently. Most existing end-to …
autonomous driving and has attracted increasing attention recently. Most existing end-to …
Is ego status all you need for open-loop end-to-end autonomous driving?
End-to-end autonomous driving recently emerged as a promising research direction to
target autonomy from a full-stack perspective. Along this line many of the latest works follow …
target autonomy from a full-stack perspective. Along this line many of the latest works follow …
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 …