Interest Point Detection

8 papers with code • 0 benchmarks • 1 datasets

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Greatest papers with code

SuperPoint: Self-Supervised Interest Point Detection and Description

magicleap/SuperGluePretrainedNetwork 20 Dec 2017

This paper presents a self-supervised framework for training interest point detectors and descriptors suitable for a large number of multiple-view geometry problems in computer vision.

Domain Adaptation Homography Estimation

R2D2: Reliable and Repeatable Detector and Descriptor

naver/r2d2 NeurIPS 2019

We thus propose to jointly learn keypoint detection and description together with a predictor of the local descriptor discriminativeness.

Atari Games Camera Localization +3

USIP: Unsupervised Stable Interest Point Detection from 3D Point Clouds

lijx10/USIP 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.

Interest Point Detection

R2D2: Repeatable and Reliable Detector and Descriptor

naver/kapture 14 Jun 2019

In this work, we argue that salient regions are not necessarily discriminative, and therefore can harm the performance of the description.

Interest Point Detection Keypoint Detection +1

Neural Outlier Rejection for Self-Supervised Keypoint Learning

TRI-ML/KP2D 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.

Homography Estimation Keypoint Detection +2

DELTAS: Depth Estimation by Learning Triangulation And densification of Sparse points

magicleap/DELTAS ECCV 2020

Cost volume based approaches employing 3D convolutional neural networks (CNNs) have considerably improved the accuracy of MVS systems.

Interest Point Detection Monocular Depth Estimation +1

SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning

uzh-rpg/sips2_open 3 May 2018

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.

Interest Point Detection Pose Estimation +1