OW-Mamba: Mamba for open world object detection - Sun, Heyuan (Nanyang Technological University, 2024)
Object detection is a fundamental task in computer vision, and recently, a more challenging variant known as open-world object detection has gained attention. This task involves not only identifying novel, unknown objects but also incrementally learning to classify them as labels become available. Two notable approaches, Open World Detection Transformer (OWDETR) and Localization and Identification Cascade Detection Transformer (CAT), have been proposed to address this challenge. However, these methods are prone to generating false unknown objects and are computationally expensive, especially with high-resolution images. Additionally, there is significant room for improvement in detecting novel objects.