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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 2130 of 339 papers

TitleStatusHype
Center Direction Network for Grasping Point Localization on ClothsCode1
Dense Interspecies Face EmbeddingCode1
BPFNet: A Unified Framework for Bimodal Palmprint Alignment and FusionCode1
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud RegistrationCode1
A Novel Dataset for Keypoint Detection of quadruped Animals from ImagesCode1
CapeX: Category-Agnostic Pose Estimation from Textual Point ExplanationCode1
2.5D U-Net with Depth Reduction for 3D CryoET Object IdentificationCode1
Cascaded Pyramid Network for Multi-Person Pose EstimationCode1
Centroid Distance Keypoint Detector for Colored Point CloudsCode1
Enhancing Scene Coordinate Regression with Efficient Keypoint Detection and Sequential InformationCode1
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