198 citations · 605 across the 6 of their papers we have counts for
6 papers
Physics Informed Neural Fields for Smoke Reconstruction with Sparse Data
Mengyu Chu, Lingjie Liu, Quan Zheng +4
High-fidelity reconstruction of fluids from sparse multiview RGB videos remains a formidable challenge due to the complexity of the underlying physics as well as complex occlusion…
Volumetric Isosurface Rendering with Deep Learning-Based Super-Resolution
Sebastian Weiss, Mengyu Chu, Nils Thuerey +1
Rendering an accurate image of an isosurface in a volumetric field typically requires large numbers of data samples. Reducing the number of required samples lies at the core of res…
A Multi-Pass GAN for Fluid Flow Super-Resolution
Maximilian Werhahn, You Xie, Mengyu Chu +1
We propose a novel method to up-sample volumetric functions with generative neural networks using several orthogonal passes. Our method decomposes generative problems on Cartesian…
Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
Mengyu Chu, You Xie, Jonas Mayer +2
Our work explores temporal self-supervision for GAN-based video generation tasks. While adversarial training successfully yields generative models for a variety of areas, temporal…
tempoGAN: A Temporally Coherent, Volumetric GAN for Super-resolution Fluid Flow
You Xie, Aleksandra Franz, Mengyu Chu +1
We propose a temporally coherent generative model addressing the super-resolution problem for fluid flows. Our work represents a first approach to synthesize four-dimensional physi…
Data-Driven Synthesis of Smoke Flows with CNN-based Feature Descriptors
Mengyu Chu, Nils Thuerey
We present a novel data-driven algorithm to synthesize high-resolution flow simulations with reusable repositories of space-time flow data. In our work, we employ a descriptor lear…