Multiple Object

Multiple object processing in computer vision and robotics focuses on accurately detecting, tracking, and manipulating multiple objects within a scene, addressing challenges like occlusion, complex motion, and diverse object appearances. Current research emphasizes developing robust and efficient algorithms, often employing transformer-based architectures and incorporating diverse feature representations (e.g., appearance, motion, and contextual information) to improve accuracy and generalization. These advancements have significant implications for various applications, including autonomous driving, robotics, and human-computer interaction, by enabling more sophisticated and reliable systems capable of interacting with complex, dynamic environments.