Cross-domain Few-annotation Industrial Dataset

This dataset, mentioned in paper MS2A: Memory Storage-to-Adaptation for Cross-domain Few-annotation Object Detection and prepared for Cross-domain Few-annotation Object Detection task, consists of two cross-domain scenarios: Indus-S to Indus-T1 and Indus-S to Indus-T2. In detail, Indus-S consists of 4614 images for training and 1153 images for validation; Indus-T1 and Indus-T2 have 269 and 432 images for validation respectively. For the training data of Indus-T1 and Indus-T2, we introduce three different settings: 10-anno, 30-anno and 50-anno. This dataset was collected from different factories with different domains and labeled using LabelMe. The objects were annotated as the part class.