Unsupervised Facial Landmark Detection
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Benchmarks
MAFL
MAFL Unaligned
300W
AFLW (Zhang CVPR 2018 crops)
AFLW Unaligned
AFLW-MTFL
Most implemented
Deep Feature Factorization For Concept Discovery
Unsupervised Part-Based Disentangling of Object Shape and Appearance
Self-supervised learning of a facial attribute embedding from video
Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance
Unsupervised Image Representation Learning with Deep Latent Particles
Papers
Unsupervised Image Representation Learning with Deep Latent Particles
We propose a new representation of visual data that disentangles object position from appearance. Our method, termed Deep Latent Particles (DLP), decomposes the visual input into low-dimensional latent ``particles'', whe…
Image ManipulationModel SelectionRepresentation LearningUnsupervised Facial Landmark Detection+1AutoLink: 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+4GANSeg: 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 Part Segmentation through Disentangling Appearance and Shape
We study the problem of unsupervised discovery and segmentation of object parts, which, as an intermediate local representation, are capable of finding intrinsic object structure and providing more explainable recognitio…
DisentanglementObjectSegmentationSemantic Segmentation+1LatentKeypointGAN: 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+2Unsupervised Learning of Landmarks by Descriptor Vector Exchange
Equivariance to random image transformations is an effective method to learn landmarks of object categories, such as the eyes and the nose in faces, without manual supervision. However, this method does not explicitly gu…
Facial Landmark DetectionObjectUnsupervised Facial Landmark Detection