A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning. (arXiv:2205.02371v1 [cs.CV])

Object tracking is one of the fundamental problems in visual recognition
tasks and has achieved significant improvements in recent years. The
achievements often come with the price of enormous hardware consumption and
expensive labor effort for consecutive labeling. A missing ingredient for
robust tracking is achieving performance with minimal modification on network
structure and semi-supervised learning intermittent labeled frames. In this
paper, we ad-dress these problems in a Bayesian tracking and detection
framework parameterized by neural network outputs. In our …

arxiv bayesian cv learning semi-supervised tracking