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DriveLM: Driving with Graph Visual Question Answering

Year: 2024

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-031-72943-0_15

Authors: Chonghao Sima, Katrin Renz, Kashyap Chitta, Li Chen, Hanxue Zhang, Chengen Xie, Jens Beißwenger, Ping Luo, Andreas Geiger, Hongyang Li

Institutions: Shanghai Artificial Intelligence Laboratory, University of Hong Kong, Tübingen AI Center, University of Tübingen

Language: English

Topic: Autonomous Vehicle Technology and Safety

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: International Max Planck Research School for Environmental, Cellular and Molecular Microbiology, Deutsche Forschungsgemeinschaft, National Natural Science Foundation of China, Bundesministerium für Bildung und Forschung, International Max Planck Research School for Advanced Methods in Process and Systems Engineering

Awards: G1562512020, G5113843979, SFB 1233: Robustheit des Sehens Prinzipien der Inferenz und neuronale Mechanismen, Verbundprojekt TUEAI: Tübingen AI Center, EXC 2064: Maschinelles Lernen: Neue Perspektiven für die Wissenschaft, G817300853, G864726782

OpenAlex ID: W4404820176

FWCI: 177.2

Cites: 59

Cited by: 448

Related to: 10