Grid-centric traffic scenario perception for autonomous driving: A comprehensive review
Grid-centric perception is a crucial field for mobile robot perception and navigation.
Nonetheless, grid-centric perception is less prevalent than object-centric perception as …
Nonetheless, grid-centric perception is less prevalent than object-centric perception as …
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 …
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 …
Maptr: Structured modeling and learning for online vectorized hd map construction
High-definition (HD) map provides abundant and precise environmental information of the
driving scene, serving as a fundamental and indispensable component for planning in …
driving scene, serving as a fundamental and indispensable component for planning in …
Symphonize 3d semantic scene completion with contextual instance queries
Abstract 3D Semantic Scene Completion (SSC) has emerged as a nascent and pivotal
undertaking in autonomous driving aiming to predict the voxel occupancy within volumetric …
undertaking in autonomous driving aiming to predict the voxel occupancy within volumetric …
Lane graph as path: Continuity-preserving path-wise modeling for online lane graph construction
Online lane graph construction is a promising but challenging task in autonomous driving.
Previous methods usually model the lane graph at the pixel or piece level, and recover the …
Previous methods usually model the lane graph at the pixel or piece level, and recover the …
Lidar2map: In defense of lidar-based semantic map construction using online camera distillation
Semantic map construction under bird's-eye view (BEV) plays an essential role in
autonomous driving. In contrast to camera image, LiDAR provides the accurate 3D …
autonomous driving. In contrast to camera image, LiDAR provides the accurate 3D …
Perceive, interact, predict: Learning dynamic and static clues for end-to-end motion prediction
Motion prediction is highly relevant to the perception of dynamic objects and static map
elements in the scenarios of autonomous driving. In this work, we propose PIP, the first end …
elements in the scenarios of autonomous driving. In this work, we propose PIP, the first end …
Ppad: Iterative interactions of prediction and planning for end-to-end autonomous driving
We present a new interaction mechanism of prediction and planning for end-to-end
autonomous driving, called PPAD (Iterative Interaction of Prediction and Planning …
autonomous driving, called PPAD (Iterative Interaction of Prediction and Planning …
RayFormer: Improving Query-Based Multi-Camera 3D Object Detection via Ray-Centric Strategies
The recent advances in query-based multi-camera 3D object detection are featured by
initializing object queries in the 3D space, and then sampling features from perspective-view …
initializing object queries in the 3D space, and then sampling features from perspective-view …