Interest Point Detection
11 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Interest Point Detection
Hollywood 3D dataset
Latest papers
Rethinking Low-level Features for Interest Point Detection and Description
Although great efforts have been made for interest point detection and description, the current learning-based methods that use high-level features from the higher layers of Convolutional Neural Networks (CNN) do not completely outperform the conventional methods.
ZippyPoint: Fast Interest Point Detection, Description, and Matching through Mixed Precision Discretization
menelaoskanakis/zippypoint
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Efficient detection and description of geometric regions in images is a prerequisite in visual systems for localization and mapping.
MultiPoint: Cross-spectral registration of thermal and optical aerial imagery
ethz-asl/multipoint
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2020 Conference on Robot Learning 2020
This model is then deployed for fast and accurate online interest point detection.
DELTAS: Depth Estimation by Learning Triangulation And densification of Sparse points
magicleap/DELTAS
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ECCV 2020
Cost volume based approaches employing 3D convolutional neural networks (CNNs) have considerably improved the accuracy of MVS systems.
CAE-LO: LiDAR Odometry Leveraging Fully Unsupervised Convolutional Auto-Encoder for Interest Point Detection and Feature Description
As an important technology in 3D mapping, autonomous driving, and robot navigation, LiDAR odometry is still a challenging task.
Neural Outlier Rejection for Self-Supervised Keypoint Learning
TRI-ML/KP2D
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ICLR 2020
By making the sampling of inlier-outlier sets from point-pair correspondences fully differentiable within the keypoint learning framework, we show that are able to simultaneously self-supervise keypoint description and improve keypoint matching.
R2D2: Reliable and Repeatable Detector and Descriptor
We thus propose to jointly learn keypoint detection and description together with a predictor of the local descriptor discriminativeness.
R2D2: Repeatable and Reliable Detector and Descriptor
In this work, we argue that salient regions are not necessarily discriminative, and therefore can harm the performance of the description.
USIP: Unsupervised Stable Interest Point Detection from 3D Point Clouds
lijx10/USIP
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ICCV 2019
In this paper, we propose the USIP detector: an Unsupervised Stable Interest Point detector that can detect highly repeatable and accurately localized keypoints from 3D point clouds under arbitrary transformations without the need for any ground truth training data.
SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning
In certain cases, our detector is able to obtain an equivalent amount of inliers with as little as 60% of the amount of points of other detectors.
