Image-based table cell detection: a new dataset and an improved detection method.

Table detection has been an interesting and challenging problem in the field of document analyses. Object detection algorithms such as Faster-RCNN has been exploited so many times to detect tables in the documents. This is just another experiment but with a different architecture which is Mask_RCNN.

Using deep-leaning detect tables in the documet image

deeplabv3plus (Google's new algorithm for semantic segmentation) in keras：Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Table Detection using Deep Learning FasterRCNN

Code for paper Unsupervised Object Segmentation by Redrawing

Tools for extracting tables and texts from papers

Tools for extracting tables and texts from papers

Activation Maps (Layers Outputs) and Gradients in Keras.

tableGAN is a synthetic data generation technique (Data Synthesis based on Generative Adversarial Networks paper) based on Generative Adversarial Network architecture (DCGAN).

An awesome semantic segmentation model that runs in real time

Symbol detection in online handwritten graphics using Faster R-CNN

Text recognition combo - CRAFT + CRNN

Code for 'PolarMask: Single Shot Instance Segmentation with Polar Representation'

A repository with anonymized invoices