7 papers
BEVWorld: A Multimodal World Simulator for Autonomous Driving via Scene-Level BEV Latents
Yumeng Zhang, Shi Gong, Kaixin Xiong +7
World models have attracted increasing attention in autonomous driving for their ability to forecast potential future scenarios. In this paper, we propose BEVWorld, a novel framewo…
LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating
Deguo Xia, Weiming Zhang, Xiyan Liu +6
An up-to-date city-scale lane-level map is an indispensable infrastructure and a key enabling technology for ensuring the safety and user experience of autonomous driving systems.…
MONOPOLY: Learning to Price Public Facilities for Revaluing Private Properties with Large-Scale Urban Data
Miao Fan, Jizhou Huang, An Zhuo +3
The value assessment of private properties is an attractive but challenging task which is widely concerned by a majority of people around the world. A prolonged topic among us is `…
DuMapper: Towards Automatic Verification of Large-Scale POIs with Street Views at Baidu Maps
Miao Fan, Jizhou Huang, Haifeng Wang
With the increased popularity of mobile devices, Web mapping services have become an indispensable tool in our daily lives. To provide user-satisfied services, such as location sea…
HGAMN: Heterogeneous Graph Attention Matching Network for Multilingual POI Retrieval at Baidu Maps
Jizhou Huang, Haifeng Wang, Yibo Sun +4
The increasing interest in international travel has raised the demand of retrieving point of interests in multiple languages. This is even superior to find local venues such as res…
Exploring the Causality of End-to-End Autonomous Driving
Jiankun Li, Hao Li, Jiangjiang Liu +6
Deep learning-based models are widely deployed in autonomous driving areas, especially the increasingly noticed end-to-end solutions. However, the black-box property of these model…