Anchor Based Detection

Anchor-based detection is a core technique in object detection, aiming to precisely locate and classify objects within images or videos by assigning predefined "anchor" boxes to potential targets. Recent research emphasizes improving anchor selection and assignment, exploring methods like diffusion models to generate more effective anchors and dynamically adjusting label assignments based on predicted Intersection over Union (IoU) scores. These advancements are driving improvements in various applications, including autonomous driving (3D object detection), surgical action recognition, and even nuanced tasks like detecting opinionated statements in news broadcasts. The overall goal is to enhance accuracy and robustness, particularly in challenging scenarios with complex temporal dynamics or fine-grained classes.