Universal Visual Perception

Universal visual perception aims to create single, adaptable computer vision systems capable of performing diverse tasks, such as object detection, segmentation, and pose estimation, across various domains. Current research focuses on developing unified model architectures, often based on transformers, that can process visual data and associated textual prompts to achieve this versatility through techniques like few-shot learning and point-based representations. This pursuit promises to significantly streamline the development of computer vision applications and improve their generalizability, impacting fields ranging from automated animal monitoring to broader image understanding tasks.