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Found 6 papers, 2 papers with code
On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks
Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data.
Is my Depth Ground-Truth Good Enough? HAMMER -- Highly Accurate Multi-Modal Dataset for DEnse 3D Scene Regression
Depth estimation is a core task in 3D computer vision.
HDD-Net: Hybrid Detector Descriptor with Mutual Interactive Learning
Local feature extraction remains an active research area due to the advances in fields such as SLAM, 3D reconstructions, or AR applications.
A Novel Representation of Parts for Accurate 3D Object Detection and Tracking in Monocular Images
We present a method that estimates in real-time and under challenging conditions the 3D pose of a known object.
Learning to Assign Orientations to Feature Points
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.
TILDE: A Temporally Invariant Learned DEtector
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 are surprisingly sensitive.
