Why do most facial recognition algorithms use a hypersphere manifold?

This page summarizes the projects mentioned and recommended in the original post on /r/deeplearning

Our great sponsors
  • WorkOS - The modern identity platform for B2B SaaS
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • SaaSHub - Software Alternatives and Reviews
  • sphereface

    Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17.

  • Code for https://arxiv.org/abs/1704.08063 found: https://github.com/wy1iu/sphereface

  • Angular-Penalty-Softmax-Losses-Pytorch

    Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

  • Code for https://arxiv.org/abs/1801.09414 found: https://github.com/cvqluu/Additive-Margin-Softmax-Loss-Pytorch

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

    WorkOS logo
  • insightface

    State-of-the-art 2D and 3D Face Analysis Project

  • Code for https://arxiv.org/abs/1801.07698 found: https://github.com/deepinsight/insightface

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts