Multi-Class 3D Object Detection with Single-Class Supervision. (arXiv:2205.05703v1 [cs.CV])

Web: http://arxiv.org/abs/2205.05703

While multi-class 3D detectors are needed in many robotics applications,
training them with fully labeled datasets can be expensive in labeling cost. An
alternative approach is to have targeted single-class labels on disjoint data
samples. In this paper, we are interested in training a multi-class 3D object
detection model, while using these single-class labeled data. We begin by
detailing the unique stance of our "Single-Class Supervision" (SCS) setting
with respect to related concepts such as partial supervision and semi
supervision. …

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