Zobrazeno 1 - 10
of 226
pro vyhledávání: '"Peng Lihui"'
The multi-modal perception methods are thriving in the autonomous driving field due to their better usage of complementary data from different sensors. Such methods depend on calibration and synchronization between sensors to get accurate environment
Externí odkaz:
http://arxiv.org/abs/2412.10033
Autor:
Ming, Ruibo, Wu, Jingwei, Huang, Zhewei, Ju, Zhuoxuan, HU, Jianming, Peng, Lihui, Zhou, Shuchang
Recent advances in auto-regressive large language models (LLMs) have shown their potential in generating high-quality text, inspiring researchers to apply them to image and video generation. This paper explores the application of LLMs to video contin
Externí odkaz:
http://arxiv.org/abs/2412.03758
Multi-modal object detection in autonomous driving has achieved great breakthroughs due to the usage of fusing complementary information from different sensors. The calibration in fusion between sensors such as LiDAR and camera is always supposed to
Externí odkaz:
http://arxiv.org/abs/2405.16848
Future Frame Synthesis (FFS) aims to enable models to generate sequences of future frames based on existing content. This survey comprehensively reviews historical and contemporary works in FFS, including widely used datasets and algorithms. It scrut
Externí odkaz:
http://arxiv.org/abs/2401.14718
Autor:
Song, Zhihang, He, Zimin, Li, Xingyu, Ma, Qiming, Ming, Ruibo, Mao, Zhiqi, Pei, Huaxin, Peng, Lihui, Hu, Jianming, Yao, Danya, Zhang, Yi
Publikováno v:
in IEEE Transactions on Intelligent Vehicles, vol. 9, no. 1, pp. 1847-1864, Jan. 2024
Autonomous driving techniques have been flourishing in recent years while thirsting for huge amounts of high-quality data. However, it is difficult for real-world datasets to keep up with the pace of changing requirements due to their expensive and t
Externí odkaz:
http://arxiv.org/abs/2304.12205
Publikováno v:
In Applied Soft Computing December 2024 167 Part B
Publikováno v:
In Engineering Applications of Artificial Intelligence January 2025 139 Part B
Autor:
Wang, Shengnan, Hu, Delin, Zhang, Maomao, Qiu, Jiawang, Chen, Wei, Giorgio-Serchi, Francesco, Peng, Lihui, Li, Yi, Yang, Yunjie
We report a digital twin (DT) framework of electrical tomography (ET) to address the challenge of real-time quantitative multiphase flow imaging based on non-invasive and non-radioactive technologies. Multiphase flow is ubiquitous in nature, industry
Externí odkaz:
http://arxiv.org/abs/2112.05792
Publikováno v:
In Expert Systems With Applications 15 June 2024 244
Publikováno v:
In Engineering Applications of Artificial Intelligence April 2024 130