Object Detection Pipeline

Object detection pipelines aim to automatically identify and locate objects within images or point clouds, a crucial task in numerous applications like autonomous driving and security. Current research emphasizes improving accuracy and efficiency, focusing on advancements in model architectures such as transformers and YOLO variants, as well as techniques like data augmentation, pseudo-labeling, and efficient voting mechanisms for 3D object detection. These improvements are driven by the need for real-time performance and robustness across diverse datasets and challenging conditions, impacting fields ranging from robotics to medical imaging.