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Found 3 papers, 1 papers with code
Do More With What You Have: Transferring Depth-Scale from Labeled to Unlabeled Domains
We use this observed property to transfer the depth-scale from source datasets that have absolute depth labels to new target datasets that lack these measurements, enabling absolute depth predictions in the target domain.
Mind The Edge: Refining Depth Edges in Sparsely-Supervised Monocular Depth Estimation
To the best of our knowledge this paper is the first attempt to address the depth edges issue for LIDAR-supervised scenes.
You Better Look Twice: a new perspective for designing accurate detectors with reduced computations
This method can be applied on other object detection applications in scenes with a considerable amount of background and variate object sizes to reduce computations.
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