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Found 3 papers, 2 papers with code
Monitored Distillation for Positive Congruent Depth Completion
In the absence of ground truth for model selection and training, our method, termed Monitored Distillation, allows a student to exploit a blind ensemble of teachers by selectively learning from predictions that best minimize the reconstruction error for a given image.
Stereoscopic Universal Perturbations across Different Architectures and Datasets
We study the effect of adversarial perturbations of images on deep stereo matching networks for the disparity estimation task.
User Based Design and Evaluation Pipeline for Indoor Airships
Designing a controllable airship for non-expert users or preemptively evaluating the performance of desired airships has always been a very challenging problem.
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