5 papers
Adapter-Enhanced Semantic Prompting for Continual Learning
Baocai Yin, Ji Zhao, Huajie Jiang +5
Continual learning (CL) enables models to adapt to evolving data streams. A major challenge of CL is catastrophic forgetting, where new knowledge will overwrite previously acquired…
Online Temporal Fusion for Vectorized Map Construction in Mapless Autonomous Driving
Jiagang Chen, Liangliang Pan, Shunping Ji +2
To reduce the reliance on high-definition (HD) maps, a growing trend in autonomous driving is leveraging onboard sensors to generate vectorized maps online. However, current method…
General-Purpose Aerial Intelligent Agents Empowered by Large Language Models
Ji Zhao, Xiao Lin
The emergence of large language models (LLMs) opens new frontiers for unmanned aerial vehicle (UAVs), yet existing systems remain confined to predefined tasks due to hardware-softw…
Enhancing Vectorized Map Perception with Historical Rasterized Maps
Xiaoyu Zhang, Guangwei Liu, Zihao Liu +3
In autonomous driving, there is growing interest in end-to-end online vectorized map perception in bird's-eye-view (BEV) space, with an expectation that it could replace traditiona…
Leveraging Enhanced Queries of Point Sets for Vectorized Map Construction
Zihao Liu, Xiaoyu Zhang, Guangwei Liu +2
In autonomous driving, the high-definition (HD) map plays a crucial role in localization and planning. Recently, several methods have facilitated end-to-end online map construction…