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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

Showing 3140 of 339 papers

TitleStatusHype
Scale-Free Image Keypoints Using Differentiable Persistent HomologyCode1
CapeX: Category-Agnostic Pose Estimation from Textual Point ExplanationCode1
Benchmarking Fish Dataset and Evaluation Metric in Keypoint Detection -- Towards Precise Fish Morphological Assessment in Aquaculture BreedingCode1
Flowmind2Digital: The First Comprehensive Flowmind Recognition and Conversion ApproachCode1
VoxelKP: A Voxel-based Network Architecture for Human Keypoint Estimation in LiDAR DataCode1
Back to 3D: Few-Shot 3D Keypoint Detection with Back-Projected 2D FeaturesCode1
CurriculumLoc: Enhancing Cross-Domain Geolocalization through Multi-Stage RefinementCode1
EP2P-Loc: End-to-End 3D Point to 2D Pixel Localization for Large-Scale Visual LocalizationCode1
A lightweight 3D dense facial landmark estimation model from position map dataCode1
Neural Interactive Keypoint DetectionCode1
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