Region Proposal
Region proposal networks (RPNs) are a crucial component in many object detection systems, aiming to efficiently identify potential object locations within an image or other data modality (e.g., point clouds, thermal images). Current research focuses on improving RPN accuracy and efficiency through techniques like incorporating attention mechanisms, leveraging complementary information from multiple data sources (e.g., RGB, depth, thermal), and developing novel training strategies such as self-supervised learning and hard negative mining. These advancements are driving progress in various fields, including computer vision, bioinformatics (protein function prediction), and robotics (human-robot interaction), by enabling more accurate and efficient object detection and localization in diverse applications.