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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

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Showing 51–75 of 339 papers

TitleStatusHype
Keypoint CommunitiesCode1
KGNv2: Separating Scale and Pose Prediction for Keypoint-based 6-DoF Grasp Synthesis on RGB-D inputCode1
Learning Human-Object Interaction Detection using Interaction PointsCode1
Learning Keypoints from Synthetic Data for Robotic Cloth FoldingCode1
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud RegistrationCode1
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust PointCloud RegistrationCode1
Edge Weight Prediction For Category-Agnostic Pose EstimationCode1
Measure Anything: Real-time, Multi-stage Vision-based Dimensional Measurement using Segment AnythingCode1
A lightweight 3D dense facial landmark estimation model from position map dataCode1
NeMo: 3D Neural Motion Fields from Multiple Video Instances of the Same ActionCode1
Neural Interactive Keypoint DetectionCode1
Non-local Neural NetworksCode1
GoodPoint: unsupervised learning of keypoint detection and descriptionCode1
Few-shot Keypoint Detection with Uncertainty Learning for Unseen SpeciesCode1
DeepDarts: Modeling Keypoints as Objects for Automatic Scorekeeping in Darts using a Single CameraCode1
Flowmind2Digital: The First Comprehensive Flowmind Recognition and Conversion ApproachCode1
GPU optimization of the 3D Scale-invariant Feature Transform Algorithm and a Novel BRIEF-inspired 3D Fast DescriptorCode1
Back to 3D: Few-Shot 3D Keypoint Detection with Back-Projected 2D FeaturesCode1
EvoPose2D: Pushing the Boundaries of 2D Human Pose Estimation using Accelerated Neuroevolution with Weight TransferCode1
Nonlinear optical encoding enabled by recurrent linear scatteringCode1
2D3D-MATR: 2D-3D Matching Transformer for Detection-free Registration between Images and Point CloudsCode1
Deep Dual Consecutive Network for Human Pose EstimationCode1
Benchmarking Fish Dataset and Evaluation Metric in Keypoint Detection -- Towards Precise Fish Morphological Assessment in Aquaculture BreedingCode1
Deep High-Resolution Representation Learning for Human Pose EstimationCode1
Dense Interspecies Face EmbeddingCode1
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