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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 121130 of 339 papers

TitleStatusHype
Keypoint Detection and Description for Raw Bayer Images0
Keypoint Encoding for Improved Feature Extraction from Compressed Video at Low Bitrates0
Keypoints as Dynamic Centroids for Unified Human Pose and Segmentation0
GKNet: grasp keypoint network for grasp candidates detection0
Computer-Aided Automated Detection of Gene-Controlled Social Actions of Drosophila0
A Self-supervised Pressure Map human keypoint Detection Approch: Optimizing Generalization and Computational Efficiency Across Datasets0
GeoLayout: Geometry Driven Room Layout Estimation Based on Depth Maps of Planes0
CoKe: Localized Contrastive Learning for Robust Keypoint Detection0
A Self-Supervised Method for Body Part Segmentation and Keypoint Detection of Rat Images0
From Web Data to Real Fields: Low-Cost Unsupervised Domain Adaptation for Agricultural Robots0
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