Correct and Certify: A New Approach to Self-Supervised 3D-Object Perception. (arXiv:2206.11215v1 [cs.CV])

Web: http://arxiv.org/abs/2206.11215

We consider an object pose estimation and model fitting problem, where -
given a partial point cloud of an object - the goal is to estimate the object
pose by fitting a CAD model to the sensor data. We solve this problem by
combining (i) a semantic keypoint-based pose estimation model, (ii) a novel
self-supervised training approach, and (iii) a certification procedure, that
not only verifies whether the output produced by the model is correct or not,
but also flags …

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