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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 6170 of 339 papers

TitleStatusHype
Few-shot Keypoint Detection with Uncertainty Learning for Unseen SpeciesCode1
ALIKE: Accurate and Lightweight Keypoint Detection and Descriptor ExtractionCode1
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud RegistrationCode1
BPFNet: A Unified Framework for Bimodal Palmprint Alignment and FusionCode1
Keypoint CommunitiesCode1
PDC-Net+: Enhanced Probabilistic Dense Correspondence NetworkCode1
A Novel Dataset for Keypoint Detection of quadruped Animals from ImagesCode1
Learning Transferable Parameters for Unsupervised Domain AdaptationCode1
EEEA-Net: An Early Exit Evolutionary Neural Architecture SearchCode1
Greedy Offset-Guided Keypoint Grouping for Human Pose EstimationCode1
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