Comments18 pages, 3 figures. In preparation for conference submission. In version 2, clarity is improved and some typos are removed with no changes to the technical content of the paper
Transformer-Based Autonomous Driving Models and Deployment-Oriented Compression: A Survey
基于Transformer的自动驾驶模型与面向部署的压缩:综述
Juan Zhong, Yuhang Shi, Zukang Xu, Xi Chen
机构
*
Renmin University of China(中国人民大学)
;
Artificial Intelligence Innovation and Incubation Institute, Fudan University(复旦大学人工智能创新与孵化院)
;
Shanghai Academy of AI for Science(上海人工智能科学研究院)
;
Department of houmo.ai(houmo.ai部门)
D$^3$-MoE:Dual Disentangled Diffusion Mixture-of-Experts for Style-Controllable End-to-End Autonomous Driving
D$^3$-MoE:面向风格可控的端到端自动驾驶的双解耦扩散混合专家模型
Renju Feng, Rukang Wang, Ning Xi, Jianguo Yu, Liping Lu, Pan Zhou, Duanfeng Chu
机构
*
Intelligent Transportation Systems Research Center, Wuhan University of Technology(武汉理工大学智能交通系统研究中心)
;
School of Mechanical and Electronic Engineering, Wuhan University of Technology(武汉理工大学机械电子工程学院)
;
School of Computer Science and Artificial Intelligence, Wuhan University of Technology(武汉理工大学计算机科学与人工智能学院)
;
Hubei Key Laboratory of Distributed System Security, School of Cyber Science and Engineering, Huazhong University of Science and Technology(湖北省分布式系统安全重点实验室,华中科技大学网络空间安全学院)