June 6, 2024, 4:49 a.m. | Eliraz Orfaig, Inna Stainvas, Igal Bilik

cs.CV updates on arXiv.org arxiv.org

arXiv:2406.03129v1 Announce Type: new
Abstract: Vision-based autonomous driving requires reliable and efficient object detection. This work proposes a DiffusionDet-based framework that exploits data fusion from the monocular camera and depth sensor to provide the RGB and depth (RGB-D) data. Within this framework, ground truth bounding boxes are randomly reshaped as part of the training phase, allowing the model to learn the reverse diffusion process of noise addition. The system methodically enhances a randomly generated set of boxes at the inference …

abstract arxiv automotive autonomous autonomous driving cs.cv data detection driving exploits framework fusion object rgb-d sensor truth type via vision work

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