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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 101125 of 339 papers

TitleStatusHype
Explicit Box Detection Unifies End-to-End Multi-Person Pose EstimationCode1
3D3L: Deep Learned 3D Keypoint Detection and Description for LiDARsCode1
GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware SupervisionCode1
NerVE: Neural Volumetric Edges for Parametric Curve Extraction from Point CloudCode1
Fast Fourier ConvolutionCode1
Multi-Grained Contrast for Data-Efficient Unsupervised Representation LearningCode1
PosePipe: Open-Source Human Pose Estimation Pipeline for Clinical ResearchCode1
Towards High Performance Human Keypoint DetectionCode1
R2D2: Repeatable and Reliable Detector and DescriptorCode1
UKPGAN: A General Self-Supervised Keypoint DetectorCode1
RelativeNAS: Relative Neural Architecture Search via Slow-Fast LearningCode1
SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose EstimationCode1
CoFiNet: Reliable Coarse-to-fine Correspondences for Robust PointCloud RegistrationCode1
Non-local Neural NetworksCode1
PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding ModelCode0
Attend to Who You Are: Supervising Self-Attention for Keypoint Detection and Instance-Aware AssociationCode0
PifPaf: Composite Fields for Human Pose EstimationCode0
Graphite: GRAPH-Induced feaTure Extraction for Point Cloud RegistrationCode0
Conditional Negative Sampling for Contrastive Learning of Visual RepresentationsCode0
GLAMpoints: Greedily Learned Accurate Match pointsCode0
Associative Embedding: End-to-End Learning for Joint Detection and GroupingCode0
GKNet: Graph-based Keypoints Network for Monocular Pose Estimation of Non-cooperative SpacecraftCode0
Neural Outlier Rejection for Self-Supervised Keypoint LearningCode0
Pose2Seg: Detection Free Human Instance SegmentationCode0
CoDeF: Content Deformation Fields for Temporally Consistent Video ProcessingCode0
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