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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 141–150 of 339 papers

TitleStatusHype
Facial Chick Sexing: An Automated Chick Sexing System From Chick Facial Image—0
ClothesNet: An Information-Rich 3D Garment Model Repository with Simulated Clothes Environment—0
A Novel Streamline-based diffusion MRI Tractography Registration Method with Probabilistic Keypoint Detection—0
Learning Markerless Robot-Depth Camera Calibration and End-Effector Pose Estimation—0
Exploring Set Similarity for Dense Self-supervised Representation Learning—0
CLERA: A Unified Model for Joint Cognitive Load and Eye Region Analysis in the Wild—0
End-to-end learning of keypoint detector and descriptor for pose invariant 3D matching—0
End-to-end learning of keypoint detection and matching for relative pose estimation—0
Enabling Privacy-Aware AI-Based Ergonomic Analysis—0
ChartDETR: A Multi-shape Detection Network for Visual Chart Recognition—0
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