新的研究开发了可以将2D图像转换为3D内容的AI技术。
The method, called SurfNet, has great potential in the field of robotics and autonomous vehicles, as well as creating digital 3D content.
这项研究由普渡大学的唐纳德·W·费德森（Donald W.
SurfNet
The technology utilizes machine learning to analyze 2D shapes and convert them into projected three-dimensional forms. Ramani explains that the technology becomes more refined over time as the AI learns more about the shapes.
Karthik Ramani解释了这一过程，
“如果您显示了数十万个诸如汽车之类的东西的形状，如果您向其显示汽车的2D图像，它可以在3-D中重建该模型，”
在谈到Surfnet的应用时，Ramani是指由于新兴技术（例如增强和虚拟现实）引起的3D内容的需求不断上升。
Google同样提到了这一点虚拟现实设计软件；Google块。
Virtual reality
拉马尼（Ramani）设想，这项技术将随着虚拟现实的兴起而增长，并希望转型过程能很快成为瞬时。
He visualizes a future in which, “you can imagine a movie camera that is taking pictures in 2-D, but in the virtual reality world everything is appearing magically in 3-D. Inch-by-inch we are going there, and in the next five years something like this is going to happen.”
“很快，我们将处于一个人类将无法区分现实和虚拟现实的阶段。”
机器学习幻觉
除了改变二维形状外，该技术还可以将两种形状彼此合并。
Ramani解释说，Surfnet可以“拍摄两个2-D图像，并在两者之间创建3D形状，我们称之为“幻觉”。”该技术的这一元素与3D Filter launched by MyMiniFactory earlier this year。
将来，研究人员将寻求进一步开发机器学习算法以完善技术。
The research paper titled ‘SurfNet: Generating 3D shape surfaces using deep residual networks’ has been在这里出版。
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特色图像显示将飞机映射到3D模型中。图像通过普渡大学。
