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README.md
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## Introduction
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we develop a high-efficiency framework for pixel-level face parsing annotating and construct a new large-scale **La**ndmark guided face **Pa**rsing dataset (LaPa) for face parsing. It consists of more than 22,000 facial images with abundant variations in expression, pose and occlusion, and each image of LaPa is provided with a 11-category pixel-level label map and 106-point landmarks.
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<img src="https://github.com/lucia123/lapa-dataset/blob/master/sample.png" width="600" alt="picture"/>
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<center>Fig. 1: Annotation examples of the proposed LaPa dataset.</center>
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## Citation
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If you use our datasets, please cite the following paper:
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## Introduction
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we develop a high-efficiency framework for pixel-level face parsing annotating and construct a new large-scale **La**ndmark guided face **Pa**rsing dataset (LaPa) for face parsing. It consists of more than 22,000 facial images with abundant variations in expression, pose and occlusion, and each image of LaPa is provided with a 11-category pixel-level label map and 106-point landmarks.
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## Citation
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If you use our datasets, please cite the following paper:
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