Instance Segmentation XXL-CT Challenge of a Historic Airplane
This addresses the challenge of non-destructive testing for compound objects in XXL-CT imagery, but it is incremental as it focuses on assessing existing methods rather than introducing new ones.
The paper tackled the problem of instance segmentation in XXL-CT images of a historic airplane, where the challenge involved automatic or interactive methods to delineate components like screws and rivets, and it reported the outcomes and limitations of submitted methods without specifying concrete numerical results.
Instance segmentation of compound objects in XXL-CT imagery poses a unique challenge in non-destructive testing. This complexity arises from the lack of known reference segmentation labels, limited applicable segmentation tools, as well as partially degraded image quality. To asses recent advancements in the field of machine learning-based image segmentation, the "Instance Segmentation XXL-CT Challenge of a Historic Airplane" was conducted. The challenge aimed to explore automatic or interactive instance segmentation methods for an efficient delineation of the different aircraft components, such as screws, rivets, metal sheets or pressure tubes. We report the organization and outcome of this challenge and describe the capabilities and limitations of the submitted segmentation methods.