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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 326339 of 339 papers

TitleStatusHype
Unconstrained Face Recognition using ASURF and Cloud-Forest Classifier optimized with VLAD0
Unsupervised Deep Learning-based Keypoint Localization Estimating Descriptor Matching Performance0
Unsupervised Model Diagnosis0
Unsupervised training of keypoint-agnostic descriptors for flexible retinal image registration0
Unsupervised Visual Attention and Invariance for Reinforcement Learning0
UR2KiD: Unifying Retrieval, Keypoint Detection, and Keypoint Description without Local Correspondence Supervision0
USEEK: Unsupervised SE(3)-Equivariant 3D Keypoints for Generalizable Manipulation0
Utilizing Radiomic Feature Analysis For Automated MRI Keypoint Detection: Enhancing Graph Applications0
Video-based Surgical Tool-tip and Keypoint Tracking using Multi-frame Context-driven Deep Learning Models0
Viewpoints and Keypoints0
Vision Aided Environment Semantics Extraction and Its Application in mmWave Beam Selection0
Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image0
Weakly-supervised High-fidelity Ultrasound Video Synthesis with Feature Decoupling0
Weakly Supervised Learning of Keypoints for 6D Object Pose Estimation0
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