Multi Instance

Multi-instance registration aims to identify and locate multiple occurrences of a known object (the "source") within a complex scene (the "target"). Current research focuses on improving the robustness and efficiency of this process, particularly in cluttered environments, using techniques like instance-aware feature extraction, contrastive learning for correspondence refinement, and iterative registration strategies that progressively eliminate outliers. These advancements are crucial for applications such as 3D scene understanding, robotics, and autonomous navigation, enabling more accurate and efficient object recognition and localization in challenging real-world scenarios.