Object detection with deep neural networks under constrained scenarios - Zhang, Gongjie (Nanyang Technological University, 2023)
Object detection, which aims to recognize and locate objects within images using bounding boxes, is one of the most fundamental tasks in computer vision. Object detection forms the basis for many other computer vision tasks and has extensive use cases, such as autonomous driving, surveillance, robotic vision, etc. In the past ten years, object detection has made unprecedented progress with the development of deep neural networks. Compared with prior arts that adopt handcrafted features, modern object detectors benefit from the strong feature representations produced by deep neural networks, and have achieved strong performance on many challenging generic object detection benchmarks, such as MSCOCO and OpenImages.