Visual Attribute Extraction And Product Tagging

via “object-instance-detection-with-dense-attributes”

108K images with dense scene graphs and 5.4M region descriptions.

Unique: Combines 3.8M object instances with 2.8M attribute annotations in a unified dataset, enabling training of attribute-aware detection models. Attributes are structured as key-value pairs and grounded to specific instances, creating dense supervision for learning visual properties beyond category labels.

vs others: Richer attribute annotations than COCO (which has minimal attributes) and larger scale than fine-grained datasets like CUB-200 (11K images); enables training attribute-aware detection at scale