activity
20152023
most citedDeep learning in remote sensing: a review

3.2k citations · 3.2k across the 17 of their papers we have counts for

collaborators

36 papers

cs.CV2023

HOC-Search: Efficient CAD Model and Pose Retrieval from RGB-D Scans

Stefan Ainetter, Sinisa Stekovic, Friedrich Fraundorfer +1

We present an automated and efficient approach for retrieving high-quality CAD models of objects and their poses in a scene captured by a moving RGB-D camera. We first investigate…

cs.CV2023

S-TREK: Sequential Translation and Rotation Equivariant Keypoints for local feature extraction

Emanuele Santellani, Christian Sormann, Mattia Rossi +2

In this work we introduce S-TREK, a novel local feature extractor that combines a deep keypoint detector, which is both translation and rotation equivariant by design, with a light…

cs.CV2023

GAFAR: Graph-Attention Feature-Augmentation for Registration A Fast and Light-weight Point Set Registration Algorithm

Ludwig Mohr, Ismail Geles, Friedrich Fraundorfer

Rigid registration of point clouds is a fundamental problem in computer vision with many applications from 3D scene reconstruction to geometry capture and robotics. If a suitable i…

cs.CV2022

Automatically Annotating Indoor Images with CAD Models via RGB-D Scans

Stefan Ainetter, Sinisa Stekovic, Friedrich Fraundorfer +1

We present an automatic method for annotating images of indoor scenes with the CAD models of the objects by relying on RGB-D scans. Through a visual evaluation by 3D experts, we sh…

cs.CV2022★ 1 cited

DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo

Christian Sormann, Emanuele Santellani, Mattia Rossi +2

We propose a novel approach for deep learning-based Multi-View Stereo (MVS). For each pixel in the reference image, our method leverages a deep architecture to search for the corre…

cs.CV2022

FCDSN-DC: An Accurate and Lightweight Convolutional Neural Network for Stereo Estimation with Depth Completion

Dominik Hirner, Friedrich Fraundorfer

We propose an accurate and lightweight convolutional neural network for stereo estimation with depth completion. We name this method fully-convolutional deformable similarity netwo…