Deformable Capsules for Object Detection [article]

Rodney Lalonde, Naji Khosravan, Ulas Bagci
2022 arXiv   pre-print
In this study, we introduce a new family of capsule networks, deformable capsules (DeformCaps), to address a very important problem in computer vision: object detection. We propose two new algorithms associated with our DeformCaps: a novel capsule structure (SplitCaps), and a novel dynamic routing algorithm (SE-Routing), which balance computational efficiency with the need for modeling a large number of objects and classes, which have never been achieved with capsule networks before. We
more » ... ate that the proposed methods allow capsules to efficiently scale-up to large-scale computer vision tasks for the first time, and create the first-ever capsule network for object detection in the literature. Our proposed architecture is a one-stage detection framework and obtains results on MS COCO which are on-par with state-of-the-art one-stage CNN-based methods, while producing fewer false positive detections, generalizing to unusual poses/viewpoints of objects.
arXiv:2104.05031v2 fatcat:mugmaoq4hfaa5edgyoj7qdb4s4