Papers Unsupervised Human Pose Estimation
“Unsupervised Human Pose Estimation” 태그가 달린 논문 13편 · 필터 해제
Unsupervised Keypoints from Pretrained Diffusion Models
Unsupervised learning of keypoints and landmarks has seen significant progress with the help of modern neural network architectures, but performance is yet to match the supervised counterpart, making their practicability…
DenoisingUnsupervised Human Pose EstimationUnsupervised KeypointsAutoLink: 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+4ElePose: Unsupervised 3D Human Pose Estimation by Predicting Camera Elevation and Learning Normalizing Flows on 2D Poses
Human pose estimation from single images is a challenging problem that is typically solved by supervised learning. Unfortunately, labeled training data does not yet exist for many human activities since 3D annotation req…
3D Human Pose EstimationPose EstimationUnsupervised 3D Human Pose EstimationUnsupervised Human Pose EstimationSelf-Supervised Keypoint Discovery in Behavioral Videos
We propose a method for learning the posture and structure of agents from unlabelled behavioral videos. Starting from the observation that behaving agents are generally the main sources of movement in behavioral videos, …
DecoderUnsupervised Human Pose EstimationGANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation
Segmenting an image into its parts is a frequent preprocess for high-level vision tasks such as image editing. However, annotating masks for supervised training is expensive. Weakly-supervised and unsupervised methods ex…
Image AugmentationImage GenerationSegmentationUnsupervised Facial Landmark Detection+2Unsupervised Human Pose Estimation through Transforming Shape Templates
Human pose estimation is a major computer vision problem with applications ranging from augmented reality and video capture to surveillance and movement tracking. In the medical context, the latter may be an important bi…
Pose EstimationTemplate MatchingUnsupervised Human Pose EstimationLatentKeypointGAN: Controlling Images via Latent Keypoints
Generative adversarial networks (GANs) have attained photo-realistic quality in image generation. However, how to best control the image content remains an open challenge. We introduce LatentKeypointGAN, a two-stage GAN …
Image GenerationImage Quality AssessmentKeypoint DetectionUnsupervised Facial Landmark Detection+2Motion-supervised Co-Part Segmentation
Recent co-part segmentation methods mostly operate in a supervised learning setting, which requires a large amount of annotated data for training. To overcome this limitation, we propose a self-supervised deep learning m…
SegmentationUnsupervised Human Pose EstimationSCOPS: Self-Supervised Co-Part Segmentation
Parts provide a good intermediate representation of objects that is robust with respect to the camera, pose and appearance variations. Existing works on part segmentation is dominated by supervised approaches that rely o…
ObjectSegmentationUnsupervised Facial Landmark DetectionUnsupervised Human Pose Estimation+2Unsupervised Part-Based Disentangling of Object Shape and Appearance
Large intra-class variation is the result of changes in multiple object characteristics. Images, however, only show the superposition of different variable factors such as appearance or shape. Therefore, learning to dise…
Appearance TransferImage GenerationObjectPose Prediction+3Deep Feature Factorization For Concept Discovery
We propose Deep Feature Factorization (DFF), a method capable of localizing similar semantic concepts within an image or a set of images. We use DFF to gain insight into a deep convolutional neural network's learned feat…
Unsupervised Facial Landmark DetectionUnsupervised Human Pose EstimationUnsupervised KeypointsUnsupervised Discovery of Object Landmarks as Structural Representations
Deep neural networks can model images with rich latent representations, but they cannot naturally conceptualize structures of object categories in a human-perceptible way. This paper addresses the problem of learning obj…
ObjectUnsupervised Facial Landmark DetectionUnsupervised Human Pose EstimationUnsupervised Keypoint EstimationUnsupervised learning of object landmarks by factorized spatial embeddings
Learning automatically the structure of object categories remains an important open problem in computer vision. In this paper, we propose a novel unsupervised approach that can discover and learn landmarks in object cate…
ObjectUnsupervised Facial Landmark DetectionUnsupervised Human Pose EstimationUnsupervised Keypoints