Delving into the devils of bird's-eye-view perception: A review, evaluation and recipe

H Li, C Sima, J Dai, W Wang, L Lu… - … on Pattern Analysis …, 2023 - ieeexplore.ieee.org
Learning powerful representations in bird's-eye-view (BEV) for perception tasks is trending
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 …

End-to-end autonomous driving: Challenges and frontiers

L Chen, P Wu, K Chitta, B Jaeger… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
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 …

Bevfusion: Multi-task multi-sensor fusion with unified bird's-eye view representation

Z Liu, H Tang, A Amini, X Yang, H Mao… - … on robotics and …, 2023 - ieeexplore.ieee.org
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 …

Petrv2: A unified framework for 3d perception from multi-camera images

Y Liu, J Yan, F Jia, S Li, A Gao… - Proceedings of the …, 2023 - openaccess.thecvf.com
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 …

Vad: Vectorized scene representation for efficient autonomous driving

B Jiang, S Chen, Q Xu, B Liao, J Chen… - Proceedings of the …, 2023 - openaccess.thecvf.com
Autonomous driving requires a comprehensive understanding of the surrounding
environment for reliable trajectory planning. Previous works rely on dense rasterized scene …

Maptrv2: An end-to-end framework for online vectorized hd map construction

B Liao, S Chen, Y Zhang, B Jiang, Q Zhang… - International Journal of …, 2024 - Springer
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 …

Vectormapnet: End-to-end vectorized hd map learning

Y Liu, T Yuan, Y Wang, Y Wang… - … on Machine Learning, 2023 - proceedings.mlr.press
Autonomous driving systems require High-Definition (HD) semantic maps to navigate
around urban roads. Existing solutions approach the semantic mapping problem by offline …

Argoverse 2: Next generation datasets for self-driving perception and forecasting

B Wilson, W Qi, T Agarwal, J Lambert, J Singh… - arXiv preprint arXiv …, 2023 - arxiv.org
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 …

Beverse: Unified perception and prediction in birds-eye-view for vision-centric autonomous driving

Y Zhang, Z Zhu, W Zheng, J Huang, G Huang… - arXiv preprint arXiv …, 2022 - arxiv.org
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 …