May 14, 2024, 4:47 a.m. | Daniel Bogdoll, Iramm Hamdard, Lukas Namgyu R\"o{\ss}ler, Felix Geisler, Muhammed Bayram, Felix Wang, Jan Imhof, Miguel de Campos, Anushervon Tabarov,

cs.CV updates on arXiv.org arxiv.org

arXiv:2405.07865v1 Announce Type: new
Abstract: The scale-up of autonomous vehicles depends heavily on their ability to deal with anomalies, such as rare objects on the road. In order to handle such situations, it is necessary to detect anomalies in the first place. Anomaly detection for autonomous driving has made great progress in the past years but suffers from poorly designed benchmarks with a strong focus on camera data. In this work, we propose AnoVox, the largest benchmark for ANOmaly detection …

abstract anomaly anomaly detection arxiv autonomous autonomous driving autonomous vehicles benchmark cs.cv cs.ro deal detection driving multimodal objects scale scale-up type vehicles

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