Instance Detection

Instance detection, a core computer vision task, aims to precisely locate and delineate individual objects within an image or scene, going beyond simple object classification. Current research emphasizes improving accuracy and efficiency in challenging scenarios like dense crowds and occlusions, often leveraging advanced architectures like those incorporating density maps and relation modules to better handle complex spatial relationships between objects. This work is driven by the need for robust instance detection in diverse applications, including robotics, autonomous driving, and medical image analysis, where accurate object identification is crucial for effective decision-making. Recent advancements focus on reducing reliance on large labeled datasets through techniques such as self-supervised learning and synthetic data generation.