Probabilistic object detection via deep ensembles
Probabilistic object detection is the task of detecting objects in images and accurately
quantifying the spatial and semantic uncertainties of the detection. Measuring uncertainty is …
quantifying the spatial and semantic uncertainties of the detection. Measuring uncertainty is …
What can robotics research learn from computer vision research?
The fields of computer vision and robotics are both children of the artificial intelligence
program that was spawned by the Dartmouth Conference in 1956. In recent decades the …
program that was spawned by the Dartmouth Conference in 1956. In recent decades the …
An uncertainty estimation framework for probabilistic object detection
In this paper, we introduce a new technique that combines two popular methods to estimate
uncertainty in object detection. Quantifying uncertainty is critical in realworld robotic …
uncertainty in object detection. Quantifying uncertainty is critical in realworld robotic …
Probabilistic object detection with an ensemble of experts
D Miller - Computer Vision–ECCV 2020 Workshops: Glasgow …, 2020 - Springer
Probabilistic object detection requires detectors to localise and classify objects in an image,
while also providing accurate spatial and semantic uncertainty. In this work, we present an …
while also providing accurate spatial and semantic uncertainty. In this work, we present an …
[PDF][PDF] Probabilistic Object Detection via Deep Ensembles
WJ Beksi - researchgate.net
Probabilistic object detection is the task of detecting objects in images and accurately
quantifying the spatial and semantic uncertainties of the detection. Measuring uncertainty is …
quantifying the spatial and semantic uncertainties of the detection. Measuring uncertainty is …