arxiv: https://arxiv.org/abs/2111.15664 Key Points visual document understanding model which does OCR + downstream task in one step with a single end-to-end model outputs are generative, and formatted to be convertible to JSON, which makes this architecture highly compatible to various downstream tasks. present SynthDoG, a synthetic document image generator used in Read more…
arxiv: https://arxiv.org/abs/2106.11539 this work proposes a backbone for visual document understanding domain. It uses text, visual, spatial features. Key points use text, visual, spatial features at each encoding layer, keep feeding in visual and spatial features on the input side. This has the ‘residual’ connection effect. text and visual features Read more…
arxiv: https://arxiv.org/abs/2012.14740 LayoutLMv2 is a work improved from LayoutLM. This line of work focues on creating a model for document understanding. The main task of this genre is to extract useful information when a document is given. In this case, it tries to extract information when a document image is Read more…