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公开(公告)号：US11410449B2
公开(公告)日：2022-08-09
申请号：US16656241
申请日：2019-10-17
发明人： Wenguan Wang , Jianbing Shen , Zhijie Zhang , Ling Shao
摘要： This disclosure relates to improved techniques for performing human parsing functions using neural network architectures. The neural network architecture can model human objects in images using a hierarchal graph of interconnected nodes that correspond to anatomical features at various levels. Multi-level inference information can be generated for each of the nodes using separate inference processes. The multi-level inference information for each node can be combined or fused to generate final predictions for each of the nodes. Parsing results may be generated based on the final predictions.
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2.发明授权公开(公告)号：US10482603B1
公开(公告)日：2019-11-19
申请号：US16451565
申请日：2019-06-25
发明人： Huazhu Fu , Jianbing Shen , Zhijie Zhang , Hang Dai , Ling Shao
摘要： This disclosure relates to improved techniques for performing image segmentation functions using neural network architectures. The neural network architecture integrates an edge guidance module and object segmentation network into a single framework for detecting target objects and performing segmentation functions. The neural network architecture can be trained to generate edge-attention representations that preserve the edge information included in images. The neural network architecture can be trained to generate multi-scale feature information that preserves and enhances object-level feature information included in images. The edge-attention representations and multi-scale feature information can be fused to generate segmentation results that identify target object boundaries with increased accuracy.
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