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Can Deep Learning be Applied to Model-Based Multi-Object Tracking?
Juliano Pinto, Georg Hess, William Ljungbergh +3
Multi-object tracking (MOT) is the problem of tracking the state of an unknown and time-varying number of objects using noisy measurements, with important applications such as auto…
Next Generation Multitarget Trackers: Random Finite Set Methods vs Transformer-based Deep Learning
Juliano Pinto, Georg Hess, William Ljungbergh +3
Multitarget Tracking (MTT) is the problem of tracking the states of an unknown number of objects using noisy measurements, with important applications to autonomous driving, survei…
Bayesian Linear Regression on Deep Representations
John Moberg, Lennart Svensson, Juliano Pinto +1
A simple approach to obtaining uncertainty-aware neural networks for regression is to do Bayesian linear regression (BLR) on the representation from the last hidden layer. Recent w…