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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 221230 of 339 papers

TitleStatusHype
FisheyeSuperPoint: Keypoint Detection and Description Network for Fisheye Images0
Multi-Instance Pose Networks: Rethinking Top-Down Pose EstimationCode1
Semi-supervised Keypoint Localization0
Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos0
Robust Automatic Monocular Vehicle Speed Estimation for Traffic Surveillance0
TransPose: Keypoint Localization via TransformerCode1
Auto Learning AttentionCode1
Fast Fourier ConvolutionCode1
Conditional Link Prediction of Category-Implicit Keypoint Detection0
UKPGAN: A General Self-Supervised Keypoint DetectorCode1
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