LS-Net: Learning to Solve Nonlinear Least Squares for Monocular Stereo
Sum-of-squares objective functions are very popular in computer vision algorithms. However, these objective functions are not always easy to optimize. The underlying assumptions made by...
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow
We introduce Recurrent All-Pairs Field Transforms (RAFT), a new deep network architecture for optical flow. RAFT extracts per-pixel features, builds multi-scale 4D correlation volumes for...
StickyPillars: Robust and Efficient Feature Matching on Point Clouds Using Graph Neural Networks
Robust point cloud registration in real-time is an important prerequisite for many
mapping and localization algorithms. Traditional methods like ICP and its derivatives tend to fail...
Online Invariance Selection for Local Feature Descriptors
To be invariant, or not to be invariant: that is the question formulated in this work about local descriptors. A limitation of current feature descriptors...
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics
Numerous deep learning applications benefit from multi-task learning with multiple regression and classification objectives. In this paper we make the observation that the performance of...
From Coarse to Fine: Robust Hierarchical Localization at Large Scale
Robust and accurate visual localization is a fundamental capability for numerous applications, such as autonomous driving, mobile robotics, or augmented reality. It remains, however, a...
UnsuperPoint: End-to-end Unsupervised Interest Point Detector and Descriptor
It is hard to create consistent ground truth data for interest points in natural images, since interest points are hard to define clearly and consistently...
BA-Net: Dense Bundle Adjustment Network
This paper introduces a network architecture to solve the structure-from-motion (SfM) problem via feature-metric bundle adjustment (BA), which explicitly enforces multi-view geometry constraints in the...
Learning Less is More – 6D Camera Localization via 3D Surface Regression
Popular research areas like autonomous driving and augmented reality have renewed the interest in image-based camera localization. In this work, we address the task of...
Deep ChArUco: Dark ChArUco Marker Pose Estimation
ChArUco boards are used for camera calibration, monocular pose estimation, and pose verification in both robotics and augmented reality. Such fiducials are detectable via traditional...