Search Results for author: Benjamin Ummenhofer

Found 10 papers, 5 papers with code

Objects With Lighting: A Real-World Dataset for Evaluating Reconstruction and Rendering for Object Relighting

1 code implementation17 Jan 2024 Benjamin Ummenhofer, Sanskar Agrawal, Rene Sepulveda, Yixing Lao, Kai Zhang, Tianhang Cheng, Stephan Richter, Shenlong Wang, German Ros

Reconstructing an object from photos and placing it virtually in a new environment goes beyond the standard novel view synthesis task as the appearance of the object has to not only adapt to the novel viewpoint but also to the new lighting conditions and yet evaluations of inverse rendering methods rely on novel view synthesis data or simplistic synthetic datasets for quantitative analysis.

Inverse Rendering Novel View Synthesis

Guaranteed Conservation of Momentum for Learning Particle-based Fluid Dynamics

1 code implementation12 Oct 2022 Lukas Prantl, Benjamin Ummenhofer, Vladlen Koltun, Nils Thuerey

We present a novel method for guaranteeing linear momentum in learned physics simulations.

Robust 3D Scene Segmentation through Hierarchical and Learnable Part-Fusion

no code implementations16 Nov 2021 Anirud Thyagharajan, Benjamin Ummenhofer, Prashant Laddha, Om J Omer, Sreenivas Subramoney

3D semantic segmentation is a fundamental building block for several scene understanding applications such as autonomous driving, robotics and AR/VR.

3D Semantic Segmentation Autonomous Driving +4

Lagrangian Fluid Simulation with Continuous Convolutions

no code implementations ICLR 2020 Benjamin Ummenhofer, Lukas Prantl, Nils Thuerey, Vladlen Koltun

We present an approach to Lagrangian fluid simulation with a new type of convolutional network.

CAM-Convs: Camera-Aware Multi-Scale Convolutions for Single-View Depth

1 code implementation CVPR 2019 Jose M. Facil, Benjamin Ummenhofer, Huizhong Zhou, Luis Montesano, Thomas Brox, Javier Civera

Single-view depth estimation suffers from the problem that a network trained on images from one camera does not generalize to images taken with a different camera model.

3D Depth Estimation Depth Prediction +1

DeepTAM: Deep Tracking and Mapping

1 code implementation ECCV 2018 Huizhong Zhou, Benjamin Ummenhofer, Thomas Brox

For mapping, we accumulate information in a cost volume centered at the current depth estimate.

Depth Estimation Depth Prediction

Global, Dense Multiscale Reconstruction for a Billion Points

no code implementations ICCV 2015 Benjamin Ummenhofer, Thomas Brox

We present a variational approach for surface reconstruction from a set of oriented points with scale information.

Surface Reconstruction

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