Global Transport for Fluid Reconstruction with Learned Self-Supervision (CVPR 2021 Video) скачать в хорошем качестве

Global Transport for Fluid Reconstruction with Learned Self-Supervision (CVPR 2021 Video)

Details at: https://ge.in.tum.de/publications/202... Authors: Erik Franz, Barbara Solenthaler, Nils Thuerey Full paper abstract: We propose a novel method to reconstruct volumetric flows from sparse views via a global transport formulation. Instead of obtaining the space-time function of the observations, we reconstruct its motion based on a single initial state. In addition, we introduce a learned self-supervision that constrains observations from unseen angles. These visual constraints are coupled via the transport constraints and a differentiable rendering step to arrive at a robust end-to-end reconstruction algorithm. This makes the reconstruction of highly realistic flow motions possible, even from only a single input view. We show with a variety of synthetic and real flows that the proposed global reconstruction of the transport process yields an improved reconstruction of the fluid motion.