Segment Object

Segment object research focuses on accurately identifying and delineating individual objects within images and videos, often aiming for class-agnostic or zero-shot capabilities. Current efforts concentrate on improving the robustness and efficiency of segmentation models, leveraging architectures like transformers and employing techniques such as prompt engineering, motion analysis, and self-supervised learning to overcome challenges posed by limited labeled data and complex scenes. This field is crucial for advancing applications in robotics, autonomous driving, medical image analysis, and remote sensing, where precise object segmentation is essential for effective decision-making and interaction with the environment.