Anytime-Lidar: Deadline-aware 3D Object Detection. (arXiv:2208.12181v1 [cs.CV])

In this work, we present a novel scheduling framework enabling anytime
perception for deep neural network (DNN) based 3D object detection pipelines.
We focus on computationally expensive region proposal network (RPN) and
per-category multi-head detector components, which are common in 3D object
detection pipelines, and make them deadline-aware. We propose a scheduling
algorithm, which intelligently selects the subset of the components to make
effective time and accuracy trade-off on the fly. We minimize accuracy loss of
skipping some of the …

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