Methods › Computer Vision › Face Recognition Models › MagFace

MagFace

7 papers tagged archive 2025-07-28

Introduced by Qiang Meng et al. in MagFace: A Universal Representation for Face Recognition and Quality Assessment

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

MagFace is a category of losses for face recognition that learn a universal feature embedding whose magnitude can measure the quality of a given face. Under the new loss, it can be proven that the magnitude of the feature embedding monotonically increases if the subject is more likely to be recognized. In addition, MagFace introduces an adaptive mechanism to learn a well-structured within-class feature distributions by pulling easy samples to class centers while pushing hard samples away. For face recognition, MagFace helps prevent model overfitting on noisy and low-quality samples by an adaptive mechanism to learn well-structured within-class feature distributions -- by pulling easy samples to class centers while pushing hard samples away.

PaperSource

Papers archive 2025-07-28

7 shown of 7, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

11 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Face Recognition7
Face Image Quality2
Clustering1
Data Augmentation1
Face Detection1
Face Image Quality Assessment1
Face Quality Assessement1
Face Verification1
Image Quality Assessment1
Representation Learning1
TAR1

Usage over time archive 2025-07-28

Papers per year tagged with MagFace: 2021 to 2023, peak 3 3 0 2021: 1 paper 2021 2022: 3 papers 2022 2023: 3 papers 2023
Papers per year the archive tags with this method, by the paper's archive date (7 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Face Recognition Models

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