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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 311320 of 339 papers

TitleStatusHype
SKD: Keypoint Detection for Point Clouds using Saliency Estimation0
SkelFormer: Markerless 3D Pose and Shape Estimation using Skeletal Transformers0
SKoPe3D: A Synthetic Dataset for Vehicle Keypoint Perception in 3D from Traffic Monitoring Cameras0
SKT: Integrating State-Aware Keypoint Trajectories with Vision-Language Models for Robotic Garment Manipulation0
Stereophotoclinometry Revisited0
SuperEvent: Cross-Modal Learning of Event-based Keypoint Detection0
Can Super Resolution be used to improve Human Pose Estimation in Low Resolution Scenarios?0
Template NeRF: Towards Modeling Dense Shape Correspondences from Category-Specific Object Images0
TFS Recognition: Investigating MPH]Thai Finger Spelling Recognition: Investigating MediaPipe Hands Potentials0
Towards Accurate Multi-person Pose Estimation in the Wild0
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