Omkar2118/datasets huggingface dataset:
D4LA

The D4LA dataset is a diverse benchmark for document layout analysis (DLA) derived from the RVL-CDIP dataset. It focuses on 12 document types with rich layouts, each represented by approximately 1,000 manually annotated images, while filtering out noisy, handwritten, artistic, or text-scarce images. The dataset defines 27 detailed layout categories, including DocTitle, ListText, Header, Table, Equation, and Footer, among others, catering to real-world applications.

Introducing paper: Vision Grid Transformer for Document Layout Analysis