Abstract: Systems and methods for machine learning context based confidence calibration are disclosed. In one embodiment, a processing logic may obtain an image frame; generate, with a first machine learning model, a confidence score, a bounding box, and an instance embedding corresponding to an object instance inferred from the image frame; and compute, with a second machine learning model, a calibrated confidence score for the object instance based on the instance embedding, the confidence score, and the bounding box.