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Visual Detection with Context for Document Layout Analysis

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Figure

Figure 1: Text extraction from PDF articles is generallya noisy process because of the significant inconsisten-cies in PDF publishing tools and the edit-and-republishnature of print-ready document preparation by journalpublishers and document hosting services.
Figure 2:Examples of ground-truth region labels,showing varying journal styles. Note that even whentext is illegibly small, the salient regions are visuallyapparent (e.g
Figure 3:Model for visual region detection usingFaster R-CNN. After rendering each page of a PDF to aJPEG and extracting its image features using a convolu-tional ResNet-101 network, regions of interest are pro-posed and classified by two additional network whichare trained on ground-truth labels.
Figure 4: Incorporating page and bounding box context yielded a relative improvement of 51.6% over baselineFaster R-CNN performance (23.9% absolute: 70.3% vs 46.4%)

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