Unsupervised Landmark Detection
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Benchmarks
MAFL Unaligned
Most implemented
MBW: Multi-view Bootstrapping in the Wild
Unsupervised Landmark Detection Based Spatiotemporal Motion Estimation for 4D Dynamic Medical Images
AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints
Unsupervised Learning of Object Landmarks via Self-Training Correspondence
Object landmark discovery through unsupervised adaptation
Papers
Unsupervised Discovery of Facial Landmarks and Head Pose
Unsupervised landmark and head pose estimation is fundamental in fields like biometrics, augmented reality, and emotion recognition, offering accurate spatial data without relying on labeled datasets. It enhances sca…
Emotion RecognitionHead Pose EstimationLandmark TrackingPose Estimation+1Deformation Robust Text Spotting with Geometric Prior
The goal of text spotting is to perform text detection and recognition in an end-to-end manner. Although the diversity of luminosity and orientation in scene texts has been widely studied, the font diversity and shape va…
DiversityText DetectionText SpottingUnsupervised Landmark DetectionMBW: Multi-view Bootstrapping in the Wild
Labeling articulated objects in unconstrained settings have a wide variety of applications including entertainment, neuroscience, psychology, ethology, and many fields of medicine. Large offline labeled datasets do not e…
3D ReconstructionPose EstimationSemi-supervised 2D and 3D landmark labelingUnsupervised Landmark DetectionAutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints
Structured representations such as keypoints are widely used in pose transfer, conditional image generation, animation, and 3D reconstruction. However, their supervised learning requires expensive annotation for each tar…
Pose EstimationSelf-Supervised LearningUnsupervised Facial Landmark DetectionUnsupervised Facial Landmark Detection on MAFL+4Unsupervised Landmark Detection Based Spatiotemporal Motion Estimation for 4D Dynamic Medical Images
Motion estimation is a fundamental step in dynamic medical image processing for the assessment of target organ anatomy and function. However, existing image-based motion estimation methods, which optimize the motion fiel…
AnatomyMotion EstimationUnsupervised Landmark DetectionUnsupervised Learning of Object Landmarks via Self-Training Correspondence
This paper addresses the problem of unsupervised discovery of object landmarks. We take a different path compared to that of existing works, based on 2 novel perspectives: (1) Self-training: starting from generic keypoin…
ClusteringObjectUnsupervised Landmark Detection