In Defense and Revival of Bayesian Filtering for Thermal Infrared Object Tracking

arXiv:2402.17098v1 Announce Type: new
Abstract: Deep learning-based methods monopolize the latest research in the field of thermal infrared (TIR) object tracking. However, relying solely on deep learning models to obtain better tracking results requires carefully selecting feature information that is beneficial to representing the target object and designing a reasonable template update strategy, which undoubtedly increases the difficulty of model design. Thus, recent TIR tracking methods face many challenges in complex scenarios. This paper introduces a novel Deep Bayesian Filtering …

abstract arxiv bayesian cs.cv deep learning defense designing feature filtering information research results tracking type