Unsupervised Facial Landmark Detection

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

6 leaderboard tables shown for this task, 6 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

13 shown of 13 papers with code (15 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Deep Feature Factorization For Concept Discovery
  26 Jun 2018 4 repositories listed Syntology ran 4 of 4 samples · 0 unverified · 3 pointer-only (licence)
  We propose Deep Feature Factorization (DFF), a method capable of localizing similar semantic concepts within an image or a set of images.
• Unsupervised Part-Based Disentangling of Object Shape and Appearance
  16 Mar 2019 2 repositories listed
  Large intra-class variation is the result of changes in multiple object characteristics.
• Self-supervised learning of a facial attribute embedding from video
  21 Aug 2018 2 repositories listed
  We propose a self-supervised framework for learning facial attributes by simply watching videos of a human face speaking, laughing, and moving over time.
• Unsupervised Learning of Object Landmarks through Conditional Image Generation
  20 Jun 2018 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  We propose a method for learning landmark detectors for visual objects (such as the eyes and the nose in a face) without any manual supervision.
• Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance
  18 Jun 2018 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified
  In this work we introduce Deforming Autoencoders, a generative model for images that disentangles shape from appearance in an unsupervised manner.
• Unsupervised Image Representation Learning with Deep Latent Particles
  31 May 2022 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  We propose a new representation of visual data that disentangles object position from appearance.
• AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints
  21 May 2022 1 repository listed Syntology ran 5 of 5 samples · 0 unverified
  Our key ingredients are i) an encoder that predicts keypoint locations in an input image, ii) a shared graph as a latent variable that links the same pairs of keypoints in every image, iii) an intermediate edge map that…
• GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation
  2 Dec 2021 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  Segmenting an image into its parts is a frequent preprocess for high-level vision tasks such as image editing.
• LatentKeypointGAN: Controlling Images via Latent Keypoints
  29 Mar 2021 1 repository listed
  Generative adversarial networks (GANs) have attained photo-realistic quality in image generation.
• Unsupervised Learning of Landmarks by Descriptor Vector Exchange
  18 Aug 2019 1 repository listed
  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.
• SCOPS: Self-Supervised Co-Part Segmentation
  3 May 2019 1 repository listed
  Parts provide a good intermediate representation of objects that is robust with respect to the camera, pose and appearance variations.
• Unsupervised Discovery of Object Landmarks as Structural Representations
  12 Apr 2018 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  Deep neural networks can model images with rich latent representations, but they cannot naturally conceptualize structures of object categories in a human-perceptible way.
• Unsupervised learning of object landmarks by factorized spatial embeddings
  5 May 2017 1 repository listed
  Learning automatically the structure of object categories remains an important open problem in computer vision.

Syntology lines on 7 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.