activity
20172020
most citedPatchmatchNet: Learned Multi-View Patchmatch Stereo

23 citations · 23 across the 1 of their papers we have counts for

collaborators

7 papers

cs.CV202023 cited

PatchmatchNet: Learned Multi-View Patchmatch Stereo

Fangjinhua Wang, Silvano Galliani, Christoph Vogel +2

We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for high-resolution multi-view stereo. With high computation speed and low memory requirement, Pat…

cs.CV2020

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

Arda Düzçeker, Silvano Galliani, Christoph Vogel +3

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 curr…

cs.CV2019

Self-Supervised Learning for Stereo Reconstruction on Aerial Images

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. On the downside, learning these networks requi…

cs.CV2018

Learning Energy Based Inpainting for Optical Flow

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. In this wor…

cs.CV2018

Variational 3D-PIV with Sparse Descriptors

Katrin Lasinger, Christoph Vogel, Thomas Pock +1

3D Particle Imaging Velocimetry (3D-PIV) aim to recover the flow field in a volume of fluid, which has been seeded with tracer particles and observed from multiple camera viewpoint…

cs.CV2018

3D Fluid Flow Estimation with Integrated Particle Reconstruction

Katrin Lasinger, Christoph Vogel, Thomas Pock +1

The standard approach to densely reconstruct the motion in a volume of fluid is to inject high-contrast tracer particles and record their motion with multiple high-speed cameras. A…