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Matting for mobile phone.
However the formulation of image matting is inherently ill posed.
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With the rapid development of mobile devices automatic mat ting is a very useful technique for image editing.
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Traditional methods usually employ interaction to deal with the image matting problem with trimaps and strokes and cannot run on the mobile phone in real time.
This project is not normal semantic segmentation but focus on real time protrait segmentation all the experimentals works with pytorch.
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This project provides training and testing codes to build real time human mattig on mobile phone only based cpu anather repo fast portrait segmentation show more details about whence the project requirements.
The laplacian based methods need to compute.
Image matting plays an important role in image and video editing.
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Mobile number tracker locator app is working through phone gps to track mobile or device current location and address.
Fast aimed to real time portrait segmentation at mobile phone.
Traditional methods usually employ interaction to deal with the image matting problem with trimaps and strokes and cannot run on the mobile phone in real time.
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Mobile tracker can identify your current location in seconds find out who s calling you from which location by finding the location of the phone number being used in that device.
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In this paper we propose a real time automatic deep matting approach for mobile devices.
However the formulation of image matting is inherently ill posed.
Image matting plays an important role in image and video editing.
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