作者：Liang Jiaming, Xu Chao, Cai Shengze；等
来源：NATURE MACHINE INTELLIGENCE 卷:5 期:5 页:505-517 出版时间:MAY 2023
Flow visualization technologies such as particle tracking velocimetry are broadly used for studying three-dimensional turbulent flow in natural and industrial processes. We present an end-to-end solution called graph optimal transport (GotFlow3D) to learn the three-dimensional fluid flow motion from consecutive particle images. Experimental evaluations demonstrate that GotFlow3D achieves state-of-the-art performance, which may provide deeper insight into the complex dynamics of many physical and biological systems.
