348 citations · 357 across the 5 of their papers we have counts for
5 papers · 1 filter
On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks
HyunJun Jung, Patrick Ruhkamp, Guangyao Zhai +10
Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data. The respectively used principle of measuring distances provides advantages and drawbacks…
Is my Depth Ground-Truth Good Enough? HAMMER -- Highly Accurate Multi-Modal Dataset for DEnse 3D Scene Regression
HyunJun Jung, Patrick Ruhkamp, Guangyao Zhai +9
Depth estimation is a core task in 3D computer vision. Recent methods investigate the task of monocular depth trained with various depth sensor modalities. Every sensor has its adv…
HDD-Net: Hybrid Detector Descriptor with Mutual Interactive Learning
Axel Barroso-Laguna, Yannick Verdie, Benjamin Busam +1
Local feature extraction remains an active research area due to the advances in fields such as SLAM, 3D reconstructions, or AR applications. The success in these applications relie…
Learning to Assign Orientations to Feature Points
Kwang Moo Yi, Yannick Verdie, Pascal Fua +1
We show how to train a Convolutional Neural Network to assign a canonical orientation to feature points given an image patch centered on the feature point. Our method improves feat…
TILDE: A Temporally Invariant Learned DEtector
Yannick Verdie, Kwang Moo Yi, Pascal Fua +1
We introduce a learning-based approach to detect repeatable keypoints under drastic imaging changes of weather and lighting conditions to which state-of-the-art keypoint detectors…