Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Galliani, Silvano"'
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-scale scenes but face significant challenges in large-scale scenes that
Externí odkaz:
http://arxiv.org/abs/2406.04340
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 depth in its hidden state. Ingesting multi-scale matching information, our
Externí odkaz:
http://arxiv.org/abs/2112.05126
Autor:
Düzçeker, Arda, Galliani, Silvano, Vogel, Christoph, Speciale, Pablo, Dusmanu, Mihai, Pollefeys, Marc
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. The bac
Externí odkaz:
http://arxiv.org/abs/2012.02177
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, PatchmatchNet can process higher resolution imagery and is more suited to
Externí odkaz:
http://arxiv.org/abs/2012.01411
Autor:
Ungureanu, Dorin, Bogo, Federica, Galliani, Silvano, Sama, Pooja, Duan, Xin, Meekhof, Casey, Stühmer, Jan, Cashman, Thomas J., Tekin, Bugra, Schönberger, Johannes L., Olszta, Pawel, Pollefeys, Marc
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 research. In this technical report, we present HoloLens 2 Research Mode,
Externí odkaz:
http://arxiv.org/abs/2008.11239
Autor:
Lanaras, Charis, Bioucas-Dias, José, Galliani, Silvano, Baltsavias, Emmanuel, Schindler, Konrad
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing, 146 (2018), pp. 305-319
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-resolve the lower-resolution (20 m and 60 m Ground Sampling Distance - GSD)
Externí odkaz:
http://arxiv.org/abs/1803.04271
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 work we introduce a suite of tools that exploit sparsity in both the feat
Externí odkaz:
http://arxiv.org/abs/1801.10585
Autor:
Galliani, Silvano, Lanaras, Charis, Marmanis, Dimitrios, Baltsavias, Emmanuel, Schindler, Konrad
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 goal is to spectrally enhance the input, i.e., generate an image with the
Externí odkaz:
http://arxiv.org/abs/1703.09470
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 how to measure similarity across >2 image patches. Surprisingly, no d
Externí odkaz:
http://arxiv.org/abs/1703.08836
Autor:
Marmanis, Dimitrios, Schindler, Konrad, Wegner, Jan Dirk, Galliani, Silvano, Datcu, Mihai, Stilla, Uwe
Publikováno v:
ISPRS Journal of Photogrammetry and Remote Sensing, Volume 135, January 2018, Pages 158-172, ISSN 0924-2716, https://doi.org/10.1016/j.isprsjprs.2017.11.009
We present an end-to-end trainable deep convolutional neural network (DCNN) for semantic segmentation with built-in awareness of semantically meaningful boundaries. Semantic segmentation is a fundamental remote sensing task, and most state-of-the-art
Externí odkaz:
http://arxiv.org/abs/1612.01337