Papers Unsupervised Landmark Detection
“Unsupervised Landmark Detection” 태그가 달린 논문 9편 · 필터 해제
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 DetectionObject landmark discovery through unsupervised adaptation
This paper proposes a method to ease the unsupervised learning of object landmark detectors. Similarly to previous methods, our approach is fully unsupervised in a sense that it does not require or make any use of annota…
ObjectUnsupervised Landmark DetectionSelf-supervised Learning of Interpretable Keypoints from Unlabelled Videos
We propose KeypointGAN, a new method for recognizing the pose of objects from a single image that for learning uses only unlabelled videos and a weak empirical prior on the object poses. Video frames differ primarily in …
Facial Landmark DetectionImage-to-Image TranslationKeypoint DetectionSelf-Supervised Learning+2Self-supervised Learning of Geometrically Stable Features Through Probabilistic Introspection
Self-supervision can dramatically cut back the amount of manually-labelled data required to train deep neural networks. While self-supervision has usually been considered for tasks such as image classification, in this p…
image-classificationImage ClassificationSelf-Supervised LearningUnsupervised Landmark Detection