2 papers
cs.RO2025
End-To-End Planning of Autonomous Driving in Industry and Academia: 2022-2023
Gongjin Lan, Qi Hao
This paper aims to provide a quick review of the methods including the technologies in detail that are currently reported in industry and academia. Specifically, this paper reviews…
cs.CV2024
SUSTechGAN: Image Generation for Object Detection in Adverse Conditions of Autonomous Driving
Gongjin Lan, Yang Peng, Qi Hao +1
Autonomous driving significantly benefits from data-driven deep neural networks. However, the data in autonomous driving typically fits the long-tailed distribution, in which the c…