Investigating Low Data, Confidence Aware Image Prediction on Smooth Repetitive Videos using Gaussian Processes

arXiv:2307.11259v2 Announce Type: replace
Abstract: The ability to predict future states is crucial to informed decision-making while interacting with dynamic environments. With cameras providing a prevalent and information-rich sensing modality, the problem of predicting future states from image sequences has garnered a lot of attention. Current state-of-the-art methods typically train large parametric models for their predictions. Though often able to predict with accuracy these models often fail to provide interpretable confidence metrics around their predictions. Additionally these methods are reliant …

abstract arxiv attention cameras confidence cs.cv current data decision dynamic environments future gaussian processes image information low making prediction processes sensing type videos