APEX-Net: Automatic Plot Extractor Network

• URL: http://arxiv.org/abs/2101.06217v3
• Date: Thu, 11 Feb 2021 05:03:01 GMT
• Title: APEX-Net: Automatic Plot Extractor Network
• Authors: Aalok Gangopadhyay, Prajwal Singh, Shanmuganathan Raman
• Abstract summary: We propose APEX-Net, a deep learning based framework with novel loss functions for solving the plot extraction problem. We introduce APEX-1M, a new large scale dataset which contains both the plot images and the raw data. We show visual results of our network on unseen plot images and demonstrate that it extracts the shape of the plots to a great extent.
• Score: 24.299931323012757
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Automatic extraction of raw data from 2D line plot images is a problem of great importance having many real-world applications. Several algorithms have been proposed for solving this problem. However, these algorithms involve a significant amount of human intervention. To minimize this intervention, we propose APEX-Net, a deep learning based framework with novel loss functions for solving the plot extraction problem. We introduce APEX-1M, a new large scale dataset which contains both the plot images and the raw data. We demonstrate the performance of APEX-Net on the APEX-1M test set and show that it obtains impressive accuracy. We also show visual results of our network on unseen plot images and demonstrate that it extracts the shape of the plots to a great extent. Finally, we develop a GUI based software for plot extraction that can benefit the community at large. For dataset and more information visit https://sites.google.com/view/apexnetpaper/.

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