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We develop a method for the automated detection and segmentation of Comic content, dialogue, and main comic characters in comic books, Our method is based on a deep convolutional neural network that was trained on annotated pages of the Graphic Narrative Corpus.

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johnsonman/Comic-content-detection-and-segmentation

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Comic-content-detection-and-segmentation

The project is based on Mask R-CNN for Object Detection and Segmentation

This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bounding boxes and segmentation masks for each instance of an object in the image. It's based on Feature Pyramid Network (FPN) and a ResNet101 backbone.

  • result: ( traing data 400 images, epoch: 100 )

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We develop a method for the automated detection and segmentation of Comic content, dialogue, and main comic characters in comic books, Our method is based on a deep convolutional neural network that was trained on annotated pages of the Graphic Narrative Corpus.

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