Robust Face Alignment

Description from the archive archive 2025-07-28.

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Most implemented papers archive 2025-07-28

7 shown of 7 papers with code (17 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.

• Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression
  16 Apr 2019 7 repositories listed Syntology ran 7 of 27 samples · 20 unverified · 1 pointer-only (licence)
  Then we propose a novel loss function, named Adaptive Wing loss, that is able to adapt its shape to different types of ground truth heatmap pixels.
• Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment
  5 Dec 2018 3 repositories listed
  Face Analysis Project on MXNet
• Deep Alignment Network: A convolutional neural network for robust face alignment
  6 Jun 2017 3 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Our method uses entire face images at all stages, contrary to the recently proposed face alignment methods that rely on local patches.
• Sparse Local Patch Transformer for Robust Face Alignment and Landmarks Inherent Relation Learning
  13 Mar 2022 1 repository listed
  The SLPT generates the representation of each single landmark from a local patch and aggregates them by an adaptive inherent relation based on the attention mechanism.
• Occlusion-Robust Face Alignment Using a Viewpoint-Invariant Hierarchical Network Architecture
  1 Jan 2022 1 repository listed
  The occlusion problem heavily degrades the localization performance of face alignment.
• ATF: Towards Robust Face Alignment via Leveraging Similarity and Diversity across Different Datasets
  12 Oct 2020 1 repository listed
  Face alignment is an important task in the field of multi-media.
• Latent RANSAC
  20 Feb 2018 1 repository listed
  We present a method that can evaluate a RANSAC hypothesis in constant time, i.

Syntology lines on 2 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.