376 citations · 635 across the 9 of their papers we have counts for
12 papers
ImLoc: Revisiting Visual Localization with Image-based Representation
Xudong Jiang, Fangjinhua Wang, Silvano Galliani +2
Existing visual localization methods are typically either 2D image-based, which are easy to build and maintain but limited in effective geometric reasoning, or 3D structure-based,…
R-SCoRe: Revisiting Scene Coordinate Regression for Robust Large-Scale Visual Localization
Xudong Jiang, Fangjinhua Wang, Silvano Galliani +2
Learning-based visual localization methods that use scene coordinate regression (SCR) offer the advantage of smaller map sizes. However, on datasets with complex illumination chang…
GLACE: Global Local Accelerated Coordinate Encoding
Fangjinhua Wang, Xudong Jiang, Silvano Galliani +2
Scene coordinate regression (SCR) methods are a family of visual localization methods that directly regress 2D-3D matches for camera pose estimation. They are effective in small-sc…
IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo
Fangjinhua Wang, Silvano Galliani, Christoph Vogel +1
We present IterMVS, a new data-driven method for high-resolution multi-view stereo. We propose a novel GRU-based estimator that encodes pixel-wise probability distributions of dept…
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…
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…
HoloLens 2 Research Mode as a Tool for Computer Vision Research
Dorin Ungureanu, Federica Bogo, Silvano Galliani +9
Mixed reality headsets, such as the Microsoft HoloLens 2, are powerful sensing devices with integrated compute capabilities, which makes it an ideal platform for computer vision re…
Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network
Charis Lanaras, José Bioucas-Dias, Silvano Galliani +2
The Sentinel-2 satellite mission delivers multi-spectral imagery with 13 spectral bands, acquired at three different spatial resolutions. The aim of this research is to super-resol…
Inference, Learning and Attention Mechanisms that Exploit and Preserve Sparsity in Convolutional Networks
Timo Hackel, Mikhail Usvyatsov, Silvano Galliani +2
While CNNs naturally lend themselves to densely sampled data, and sophisticated implementations are available, they lack the ability to efficiently process sparse data. In this wor…
Learned Spectral Super-Resolution
Silvano Galliani, Charis Lanaras, Dimitrios Marmanis +2
We describe a novel method for blind, single-image spectral super-resolution. While conventional super-resolution aims to increase the spatial resolution of an input image, our goa…
Learned Multi-Patch Similarity
Wilfried Hartmann, Silvano Galliani, Michal Havlena +2
Estimating a depth map from multiple views of a scene is a fundamental task in computer vision. As soon as more than two viewpoints are available, one faces the very basic question…
Classification With an Edge: Improving Semantic Image Segmentation with Boundary Detection
Dimitrios Marmanis, Konrad Schindler, Jan Dirk Wegner +3
We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmen…