Modern autonomous driving system is characterized as modular tasks in sequential order, ie, perception, prediction, and planning. In order to perform a wide diversity of tasks and …
How should we integrate representations from complementary sensors for autonomous driving? Geometry-based fusion has shown promise for perception (eg, object detection …
How should representations from complementary sensors be integrated for autonomous driving? Geometry-based sensor fusion has shown great promise for perception tasks such …
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 …
We propose a motion forecasting model that exploits a novel structured map representation as well as actor-map interactions. Instead of encoding vectorized maps as raster images, we …
H Shao, L Wang, R Chen… - Proceedings of the …, 2023 - openaccess.thecvf.com
The large-scale deployment of autonomous vehicles is yet to come, and one of the major remaining challenges lies in urban dense traffic scenarios. In such cases, it remains …
Perception and prediction are two separate modules in the existing autonomous driving systems. They interact with each other via hand-picked features such as agent bounding …
S Casas, A Sadat, R Urtasun - Proceedings of the IEEE/CVF …, 2021 - openaccess.thecvf.com
High-definition maps (HD maps) are a key component of most modern self-driving systems due to their valuable semantic and geometric information. Unfortunately, building HD maps …
This work proposes an end-to-end multi-camera 3D multi-object tracking (MOT) framework. It emphasizes spatio-temporal continuity and integrates both past and future reasoning for …