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Object pose estimation with statistical guarantees: Conformal keypoint detection and geometric uncertainty propagation
The two-stage object pose estimation paradigm first detects semantic keypoints on the
image and then estimates the 6D pose by minimizing reprojection errors. Despite performing …
image and then estimates the 6D pose by minimizing reprojection errors. Despite performing …
Adaptive bounding box uncertainties via two-step conformal prediction
Quantifying a model's predictive uncertainty is essential for safety-critical applications such
as autonomous driving. We consider quantifying such uncertainty for multi-object detection …
as autonomous driving. We consider quantifying such uncertainty for multi-object detection …
Confident object detection via conformal prediction and conformal risk control: an application to railway signaling
Deploying deep learning models in real-world certi ed systems requires the ability to provide
con dence estimates that accurately reflect their uncertainty. In this paper, we demonstrate …
con dence estimates that accurately reflect their uncertainty. In this paper, we demonstrate …
Conformal prediction for trustworthy detection of railway signals
We present an application of conformal prediction, a form of uncertainty quantification with
guarantees, to the detection of railway signals. State-of-the-art architectures are tested and …
guarantees, to the detection of railway signals. State-of-the-art architectures are tested and …
Conformal prediction for trustworthy detection of railway signals
We present an application of conformal prediction, a form of uncertainty quantification with
guarantees, to the detection of railway signals. State-of-the-art architectures are tested and …
guarantees, to the detection of railway signals. State-of-the-art architectures are tested and …