  We present TableBank, a new image-based table detection and recognition
dataset built with novel weak supervision from Word and Latex documents on the
internet. Existing research for image-based table detection and recognition
usually fine-tunes pre-trained models on out-of-domain data with a few thousand
human-labeled examples, which is difficult to generalize on real-world
applications. With TableBank that contains 417K high quality labeled tables, we
build several strong baselines using state-of-the-art models with deep neural
networks. We make TableBank publicly available and hope it will empower more
deep learning approaches in the table detection and recognition task. The
dataset and models are available at
\url{https://github.com/doc-analysis/TableBank}.
