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Found 14 papers, 6 papers with code
R-SCoRe: Revisiting Scene Coordinate Regression for Robust Large-Scale Visual Localization
Learning-based visual localization methods that use scene coordinate regression (SCR) offer the advantage of smaller map sizes.
GLACE: Global Local Accelerated Coordinate Encoding
We propose GLACE, which integrates pre-trained global and local encodings and enables SCR to scale to large scenes with only a single small-sized network.
F$^3$Loc: Fusion and Filtering for Floorplan Localization
In this paper we propose an efficient data-driven solution to self-localization within a floorplan.
F3Loc: Fusion and Filtering for Floorplan Localization
In this paper we propose an efficient data-driven solution to self-localization within a floorplan.
IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo
We present IterMVS, a new data-driven method for high-resolution multi-view stereo.
DeepVideoMVS: Multi-View Stereo on Video with Recurrent Spatio-Temporal Fusion
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.
PatchmatchNet: Learned Multi-View Patchmatch Stereo
We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for high-resolution multi-view stereo.
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Self-Supervised Learning for Stereo Reconstruction on Aerial Images
Recent developments established deep learning as an inevitable tool to boost the performance of dense matching and stereo estimation.
Learning Energy Based Inpainting for Optical Flow
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.
3D Fluid Flow Estimation with Integrated Particle Reconstruction
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.
Variational 3D-PIV with Sparse Descriptors
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
We propose a novel framework for the discretisation of multi-label problems on arbitrary, continuous domains.
Volumetric Flow Estimation for Incompressible Fluids Using the Stationary Stokes Equations
Here, we propose a variational method for 3D fluid flow estimation from multi-view data.
Large-Scale Semantic 3D Reconstruction: An Adaptive Multi-Resolution Model for Multi-Class Volumetric Labeling
We propose an adaptive multi-resolution formulation of semantic 3D reconstruction.
