ECCV 2024 Workshop
September 29, 2024 | MiCo Milano
Building safe and intelligent Autonomous Vehicles (AVs) capable of human-like reasoning is a challenging problem, pushing the limits of computer vision. Current AV systems struggle with diverse and unseen driving scenarios, necessitating a shift in research focus. Recently, multimodal large language models (MLLMs) have shown great promise in understanding human intent and solving complex problems. Such models not only showcase incredible capabilities in understanding human intent and solving complex and unstructured problems, but scale gracefully with data and compute. This workshop explores leveraging MLLMs to tackle key challenges in AV.
Time | Event |
---|---|
13:00 - 13:30 | Marco Pavone |
13:30 - 14:00 | Hongyang Li |
14:00 - 14:30 | Raquel Urtasun |
14:30 - 15:00 | Break |
15:00 - 15:30 | Long Chen |
15:30 - 16:00 | Katerina Fragkiadaki |
16:00 - 16:30 | Oral Session |
16:30 - 17:30 | Poster Session |
We welcome authors to submit their papers in two different formats: full-paper (4-8 8-14 pages) or short-abstract (2 4 pages). A full-paper should describe work that has not been published or accepted to another venue. A short-abstract can highlight work that has been published or accepted recently. Please use the ECCV 2024 paper template and follow the ECCV submission guidelines. Accepted papers will be posted on the website, but there will not be archival proceedings for this workshop.
The submission needs to be submitted to the CMT system: https://cmt3.research.microsoft.com/MLLMAV2024.