Methods › Computer Vision › Face Recognition Models › PocketNet

PocketNet

2 papers tagged archive 2025-07-28

Introduced by Fadi Boutros et al. in PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and Multi-Step Knowledge Distillation

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

PocketNet is a face recognition model family discovered through neural architecture search. The training is based on multi-step knowledge distillation.

PaperSource

Papers archive 2025-07-28

2 shown of 2, 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

9 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
Anatomy1
Computed Tomography (CT)1
Face Recognition1
Knowledge Distillation1
Lightweight Face Recognition1
Neural Architecture Search1
Organ Segmentation1
Segmentation1
Tumor Segmentation1

Usage over time archive 2025-07-28

Papers per year tagged with PocketNet: 2021 to 2024, peak 1 1 0 2021: 1 paper 2021 2022: 0 papers 2022 2023: 0 papers 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (2 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 ModelsConvolutional Neural Networks

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