来自 | 量子位
△大谷Spitzer
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一个众包平台。用户可以上传城市历史地图，将其与现实世界的坐标进行匹配，完成地理修正，并将其矢量化。
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一个时空地图服务器。能显示城市地图是如何随时间变化的。
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一个3D体验平台。运行在rǝ地图服务器之上，利用深度学习，根据有限的历史图片和地图数据重建3D建筑，创造3D体验。
以众包方式打造
重建3D模型
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用窗户、入口、楼梯这样的立面组件注释训练的RCNN，用于定位历史图像中的边框级实例。
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语义分割模型DeepLab，提供每个语义类的像素级标签。
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专门设计的神经网络，用以确保一个立面上生成的窗户之间间距相等、形状一致。同时也保证不同语义类，比如楼梯和窗户之间的一致性，使这些组件被放置到合理的位置上。
还原全球城镇，还有《微软模拟飞行》
https://ai.googleblog.com/2020/10/recreating-historical-streetscapes.html
https://re.city/#14.25/40.74094/-73.98798
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