A framework for spatiotemporal control in the tracking of visual contours

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? (2017, methodology): “Existing approaches to model uncertainty in such settings in computer vision include particle filtering and conditional random fields [3, 4].”
Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation (2020, methodology): “Traditional approaches include particle filtering and CRFs [4, 23].”
Data fusion for visual tracking with particles (2004, background): “When a specific class of objects with distinctive shape is considered and a complete model of this shape can be learned offline, contour cues are very powerful to capture the visual appearance of tracked entities [2], [3], [25], [30], [40], [44], [53].”