Delving into the devils of bird's-eye-view perception: A review, evaluation and recipe
Learning powerful representations in bird's-eye-view (BEV) for perception tasks is trending
and drawing extensive attention both from industry and academia. Conventional …
and drawing extensive attention both from industry and academia. Conventional …
Deep learning technology for construction machinery and robotics
K You, C Zhou, L Ding - Automation in construction, 2023 - Elsevier
Construction machinery and robots are essential equipment for major infrastructure. The
application of deep learning technology can improve the construction quality and alleviate …
application of deep learning technology can improve the construction quality and alleviate …
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 …
Bevfusion: Multi-task multi-sensor fusion with unified bird's-eye view representation
Multi-sensor fusion is essential for an accurate and reliable autonomous driving system.
Recent approaches are based on point-level fusion: augmenting the LiDAR point cloud with …
Recent approaches are based on point-level fusion: augmenting the LiDAR point cloud with …
Petrv2: A unified framework for 3d perception from multi-camera images
In this paper, we propose PETRv2, a unified framework for 3D perception from multi-view
images. Based on PETR, PETRv2 explores the effectiveness of temporal modeling, which …
images. Based on PETR, PETRv2 explores the effectiveness of temporal modeling, which …
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 …
Vectormapnet: End-to-end vectorized hd map learning
Autonomous driving systems require High-Definition (HD) semantic maps to navigate
around urban roads. Existing solutions approach the semantic mapping problem by offline …
around urban roads. Existing solutions approach the semantic mapping problem by offline …
Argoverse 2: Next generation datasets for self-driving perception and forecasting
We introduce Argoverse 2 (AV2)-a collection of three datasets for perception and forecasting
research in the self-driving domain. The annotated Sensor Dataset contains 1,000 …
research in the self-driving domain. The annotated Sensor Dataset contains 1,000 …
Beverse: Unified perception and prediction in birds-eye-view for vision-centric autonomous driving
In this paper, we present BEVerse, a unified framework for 3D perception and prediction
based on multi-camera systems. Unlike existing studies focusing on the improvement of …
based on multi-camera systems. Unlike existing studies focusing on the improvement of …