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Found 3 papers, 3 papers with code
MorDIFF: Recognition Vulnerability and Attack Detectability of Face Morphing Attacks Created by Diffusion Autoencoders
Creating morphing attacks is commonly either performed on the image-level or on the representation-level.
SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data
The reported evaluation results on five authentic face benchmarks demonstrated that the privacy-friendly synthetic dataset has high potential to be used for training face recognition models, achieving, for example, a verification accuracy of 91. 87\% on LFW using multi-class classification and 99. 13\% using the combined learning strategy.
PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and Multi-Step Knowledge Distillation
However, this limits the deployment of such models that contain an extremely large number of parameters to embedded and low-end devices.
Ranked #2 on
Lightweight Face Recognition
on CALFW
