E2EAD

A diversity of computer vision capabilities are all critical in building industry-level autonomous driving systems, ranging from 2D to 3D perception, prediction, planning, to scene simulation. This has inspired a surge of relevant research, growing at a fast pace with increasingly accurate and efficient new methods (e.g. BEV-based 3D detection, HDMapNet, NeRF) developed continuously. Much more than simple combination of individual independently developed methods, autonomous driving also requires synergistic integration of different functions as a whole. This however is far away from the current situation that researchers in the sub-fields of perception, planning and simulation make largely limited idea exchange and communication. This calls for a system-level perspective on the advancement of autonomous driving. This workshop aims to provide a platform where researchers from different sub-fields can focus on exchanging the frontier ideas across boundaries, leading to holistic system-aware understanding and systematic research attempts in the future. Suggested topics include, but are not limited to:

• - 3D obejct detetion
• - Traffic lane detection and HD map construction
• - End-to-end perception, prediction and planning
• - Autonomous driving environment simulation