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Keypoint Detection

Keypoint Detection is essential for analyzing and interpreting images in computer vision. It involves simultaneously detecting and localizing interesting points in an image. Keypoints, also known as interest points, are spatial locations or points in the image that define what is interesting or what stands out. They are invariant to image rotation, shrinkage, translation, distortion, etc. Keypoints examples are body joints, facial landmarks, or any other salient points in objects. Keypoints have uses in problems such as pose estimation, object detection and tracking, facial analysis, and augmented reality.

( Image credit: PifPaf: Composite Fields for Human Pose Estimation; "Learning to surf" by fotologic, license: CC-BY-2.0 )

Papers

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Showing 276–300 of 339 papers

TitleStatusHype
UR2KiD: Unifying Retrieval, Keypoint Detection, and Keypoint Description without Local Correspondence Supervision—0
Neural Outlier Rejection for Self-Supervised Keypoint LearningCode0
SKD: Keypoint Detection for Point Clouds using Saliency Estimation—0
Dynamic Convolution: Attention over Convolution KernelsCode0
Self-Supervised 3D Keypoint Learning for Ego-motion EstimationCode0
R2D2: Reliable and Repeatable Detector and DescriptorCode0
Simple and Lightweight Human Pose EstimationCode0
ViewSynth: Learning Local Features from Depth using View SynthesisCode0
Human Keypoint Detection by Progressive Context RefinementCode0
Distribution-Aware Coordinate Representation for Human Pose EstimationCode0
kPAM-SC: Generalizable Manipulation Planning using KeyPoint Affordance and Shape Completion—0
Pose Neural Fabrics SearchCode0
Learning Enhanced Resolution-wise features for Human Pose Estimation—0
Computer-Aided Automated Detection of Gene-Controlled Social Actions of Drosophila—0
A Comparison of CNN and Classic Features for Image Retrieval—0
Single-Stage Multi-Person Pose MachinesCode0
GLAMpoints: Greedily Learned Accurate Match pointsCode0
Self-supervised Learning of Interpretable Keypoints from Unlabelled Videos—0
RF-Net: An End-to-End Image Matching Network based on Receptive FieldCode0
Orthogonal Decomposition Network for Pixel-Wise Binary Classification—0
Monocular 3D Object Detection via Geometric Reasoning on Keypoints—0
KPTransfer: improved performance and faster convergence from keypoint subset-wise domain transfer in human pose estimation—0
PifPaf: Composite Fields for Human Pose EstimationCode0
PoseFix: Model-agnostic General Human Pose Refinement NetworkCode0
CrowdPose: Efficient Crowded Scenes Pose Estimation and A New BenchmarkCode0
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