VOC (Visual Object Classes)

VOC, or Visual Object Classes, is a standard benchmark used by researchers to evaluate computer vision algorithms' ability to identify and classify objects in images. It involves a dataset with annotated images containing various everyday objects like animals, vehicles, and household items. The goal is to develop and test systems that can accurately detect, locate, and categorize these objects. VOC's challenges promote improvements in object detection and recognition technologies, which are crucial for applications like autonomous vehicles, surveillance, and image search. It provides a common framework, enabling consistent comparison and progress in the field of computer vision.