Instance Perception

Instance perception, encompassing tasks like object detection and segmentation, aims to accurately identify and locate individual objects within images or videos. Current research emphasizes developing universal models capable of handling diverse instance perception tasks with limited labeled data, often employing point-based representations and leveraging techniques like mutual distillation to improve accuracy and efficiency. These advancements are crucial for various applications, including autonomous driving and industrial automation, by enabling more robust and scalable visual perception systems.