Scaled conformal prediction using aleatoric uncertainty estimates and class-wise calibration produces sharper valid prediction intervals for object detection than unscaled variants, with up to 19% higher IoU and 39% lower interval scores on driving datasets.
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Probabilistic Object Detection with Conformal Prediction
Scaled conformal prediction using aleatoric uncertainty estimates and class-wise calibration produces sharper valid prediction intervals for object detection than unscaled variants, with up to 19% higher IoU and 39% lower interval scores on driving datasets.