Facial Recognition Leveraging Generative Adversarial Networks
Face recognition performance based on deep learning heavily relies on large-scale training data, which is often difficult to acquire in practical applications. To address this challenge, this paper proposes a GAN-based data augmentation method with three key contributions: (1) a residual-embedded generator to alleviate gradient vanishing/exploding problems, (2) an Inception ResNet-V1 based FaceNet discriminator for improved adversarial training, and (3) an end-to-end framework that jointly optimizes data generation and recognition performance. Experimental results demonstrate that our approach achieves stable training dynamics and significantly improves face recognition accuracy by 12.7% on the LFW benchmark compared to baseline methods, while maintaining good generalization capability with limited training samples.
Code (0)
등록된 구현이 없습니다.
Tasks
Data AugmentationFace RecognitionSimilar Papers 제목 키워드 기반
Generative Adversarial Stacked Autoencoders for Facial Pose Normalization and Emotion Recognition
In this work, we propose a novel Generative Adversarial Stacked Autoencoder that learns to map facial expressions, with up to plus or minus 60 degrees, to an illumination invariant facial representation of 0 degrees. We …
Emotion RecognitionFacial Emotion RecognitionGeometry Guided Adversarial Facial Expression Synthesis
Facial expression synthesis has drawn much attention in the field of computer graphics and pattern recognition. It has been widely used in face animation and recognition. However, it is still challenging due to the high-…
Face RecognitionFace TransferGenerative Adversarial NetworkTexture SynthesisIdentity-Free Facial Expression Recognition using conditional Generative Adversarial Network
A novel Identity-Free conditional Generative Adversarial Network (IF-GAN) was proposed for Facial Expression Recognition (FER) to explicitly reduce high inter-subject variations caused by identity-related facial attribut…
Facial Expression RecognitionFacial Expression Recognition (FER)Generative Adversarial NetworkUsing a GAN to Generate Adversarial Examples to Facial Image Recognition
Images posted online present a privacy concern in that they may be used as reference examples for a facial recognition system. Such abuse of images is in violation of privacy rights but is difficult to counter. It is wel…
Face RecognitionGenerative Adversarial NetworkKnowledge DistillationLowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition
Facial recognition systems are increasingly deployed by private corporations, government agencies, and contractors for consumer services and mass surveillance programs alike. These systems are typically built by scraping…
Face DetectionFace Recognition