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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 3140 of 339 papers

TitleStatusHype
EP2P-Loc: End-to-End 3D Point to 2D Pixel Localization for Large-Scale Visual LocalizationCode1
Flowmind2Digital: The First Comprehensive Flowmind Recognition and Conversion ApproachCode1
DexYCB: A Benchmark for Capturing Hand Grasping of ObjectsCode1
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust PointCloud RegistrationCode1
Edge Weight Prediction For Category-Agnostic Pose EstimationCode1
Dense Interspecies Face EmbeddingCode1
ALIKE: Accurate and Lightweight Keypoint Detection and Descriptor ExtractionCode1
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud RegistrationCode1
EEEA-Net: An Early Exit Evolutionary Neural Architecture SearchCode1
CapeX: Category-Agnostic Pose Estimation from Textual Point ExplanationCode1
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