Microsoft's Table Transformer is an object-detection model based on the DETR architecture, specialized for identifying tables, columns, rows, and headers within document images. It enables accurate table structure recognition for downstream data extraction tasks. Available on Hugging Face with full model weights and Transformers integration, it is widely used in document processing pipelines and research.
Table Transformer Structure Recognition V1.1 All is an Other AI product. Automatically extracting table structures and content from document images without manual annotation. It is built as an open-source project for developers. Table Transformer Structure Recognition V1.1 All is open source under the MIT license. Table Transformer Structure Recognition V1.1 All is available on the web and API.
It is developed by Microsoft (United States), and the product first shipped in 2021. Development happens publicly on GitHub with 2.9k stars. Key capabilities include Table Detection, Structure Recognition, and Object Detection. It exposes integrations via a public API.
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