Learning to Estimate Single-View Volumetric Flow Motions without 3D Supervision

1 code implementation • 28 Feb 2023 • Erik Franz, Barbara Solenthaler, Nils Thuerey

Despite the complexity of this task, we show that it is possible to train the corresponding networks without requiring any 3D ground truth for training.

Physics Informed Neural Fields for Smoke Reconstruction with Sparse Data

no code implementations • 14 Jun 2022 • Mengyu Chu, Lingjie Liu, Quan Zheng, Erik Franz, Hans-Peter Seidel, Christian Theobalt, Rhaleb Zayer

With a hybrid architecture that separates static and dynamic contents, fluid interactions with static obstacles are reconstructed for the first time without additional geometry input or human labeling.

Global Transport for Fluid Reconstruction with Learned Self-Supervision

1 code implementation • CVPR 2021 • Erik Franz, Barbara Solenthaler, Nils Thuerey

We propose a novel method to reconstruct volumetric flows from sparse views via a global transport formulation.

tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow

2 code implementations • 29 Jan 2018 • You Xie, Erik Franz, Mengyu Chu, Nils Thuerey

We propose a temporally coherent generative model addressing the super-resolution problem for fluid flows.

Data Augmentation Generative Adversarial Network +1