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Unsupervised Facial Landmark Detection

Facial Recognition and Modelling › Facial Landmark Detection › Unsupervised Facial Landmark Detection 37 평가 기록 6 datasets

Facial landmark detection in the unsupervised setting popularized by [1]. The evaluation occurs in two stages: (1) Embeddings are first learned in an unsupervised manner (i.e. without labels); (2) A simple regressor is trained to regress landmarks from the unsupervised embedding.

[1] Thewlis, James, Hakan Bilen, and Andrea Vedaldi. "Unsupervised learning of object landmarks by factorized spatial embeddings." Proceedings of the IEEE International Conference on Computer Vision. 2017.

<span style="color:grey; opacity: 0.6">( Image credit: Unsupervised learning of object landmarks by factorized spatial embeddings )</span>

Unsupervised Facial Landmark Detection

논문

Unsupervised learning of object landmarks by factorized spatial embeddings

Unsupervised Learning of Landmarks by Descriptor Vector Exchange

Unsupervised learning of object frames by dense equivariant image labelling

AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints

Self-supervised learning of a facial attribute embedding from video

Unsupervised Discovery of Object Landmarks as Structural Representations

Unsupervised Learning of Object Landmarks through Conditional Image Generation

Unsupervised Part Segmentation through Disentangling Appearance and Shape

Unsupervised Part-Based Disentangling of Object Shape and Appearance

Deep Feature Factorization For Concept Discovery

Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance

GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation

LatentKeypointGAN: Controlling Images via Latent Keypoints

Learning Deep Representation for Face Alignment with Auxiliary Attributes

SCOPS: Self-Supervised Co-Part Segmentation

Unsupervised Image Representation Learning with Deep Latent Particles