Search Results for author: Christoph Vogel

Found 10 papers, 5 papers with code

DeepVideoMVS: Multi-View Stereo on Video with Recurrent Spatio-Temporal Fusion

1 code implementation CVPR 2021 Arda Düzçeker, Silvano Galliani, Christoph Vogel, Pablo Speciale, Mihai Dusmanu, Marc Pollefeys

We propose an online multi-view depth prediction approach on posed video streams, where the scene geometry information computed in the previous time steps is propagated to the current time step in an efficient and geometrically plausible way.

Depth Estimation Depth Prediction

Self-Supervised Learning for Stereo Reconstruction on Aerial Images

no code implementations29 Jul 2019 Patrick Knöbelreiter, Christoph Vogel, Thomas Pock

Recent developments established deep learning as an inevitable tool to boost the performance of dense matching and stereo estimation.

Self-Supervised Learning

Learning Energy Based Inpainting for Optical Flow

1 code implementation9 Nov 2018 Christoph Vogel, Patrick Knöbelreiter, Thomas Pock

Modern optical flow methods are often composed of a cascade of many independent steps or formulated as a black box neural network that is hard to interpret and analyze.

feature selection Optical Flow Estimation

3D Fluid Flow Estimation with Integrated Particle Reconstruction

1 code implementation9 Apr 2018 Katrin Lasinger, Christoph Vogel, Thomas Pock, Konrad Schindler

We show, for the first time, how to jointly reconstruct both the individual tracer particles and a dense 3D fluid motion field from the image data, using an integrated energy minimization.

3D Reconstruction Motion Estimation

Variational 3D-PIV with Sparse Descriptors

no code implementations9 Apr 2018 Katrin Lasinger, Christoph Vogel, Thomas Pock, Konrad Schindler

We propose a new method for iterative particle reconstruction (IPR), in which the locations and intensities of all particles are inferred in one joint energy minimization.

Semantic 3D Reconstruction with Finite Element Bases

no code implementations4 Oct 2017 Audrey Richard, Christoph Vogel, Maros Blaha, Thomas Pock, Konrad Schindler

We propose a novel framework for the discretisation of multi-label problems on arbitrary, continuous domains.

3D Reconstruction valid

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