U. Ramachandran

Class Geometry as Supervision for Sample-Efficient Open-World Detection

Open-world object detection requires models to recognize known categories, reject unfamiliar objects, and incorporate new classes over time. This is especially challenging in scarce-data settings such as biomedical and scientific imaging, where rare categories may have only a few annotated examples and fine-grained cla...