2 Dimensional Object Detection

Two-dimensional (2D) object detection focuses on accurately identifying and locating objects within images, a crucial step for numerous computer vision applications. Current research emphasizes improving the speed, accuracy, and robustness of 2D detectors, particularly in challenging conditions like adverse weather or low light, often leveraging architectures like YOLO and transformer-based models, and exploring techniques such as multi-sensor fusion and active learning for data efficiency. These advancements are vital for enhancing the performance of downstream tasks such as 3D object detection, autonomous driving, and robotics, where reliable 2D object detection forms a critical foundation.