FLUXSynID: A Framework for Identity-Controlled Synthetic Face Generation with Document and Live Images
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Abstract (arXiv)
Synthetic face datasets are increasingly used to overcome the limitations of real-world biometric data, including privacy concerns, demographic imbalance, and high collection costs. However, many existing methods lack fine-grained control over identity attributes and fail to produce paired, identity-consistent images under structured capture conditions. We introduce FLUXSynID, a framework for generating high-resolution synthetic face datasets along with a dataset of 14,889 synthetic identities. We generate synthetic faces with user-defined identity attribute distributions, offering both document-style and trusted live capture images. The dataset generated using the FLUXSynID framework shows improved alignment with real-world identity distributions and greater inter-class diversity compared to prior work. Our work is publicly released to support biometric research, including face recognition and morphing attack detection.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 38 of its 63 references that are in the map. First posted on arXiv 12 May 2025.
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38 of 63 references.
References · 38
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
- 2022Classifier-Free Diffusion Guidancecited by 5,847
- 2022Generative Adversarial Networkscited by 5,627
- 2024Qwen2.5 Technical Reportcited by 4,942
- 2024Scaling Rectified Flow Transformers for High-Resolution Image Synthesiscited by 4,181
- 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
- 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,300
- 2024Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scalingcited by 1,599
- 2021Alias-Free Generative Adversarial Networkscited by 1,184
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- 2022DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Modelscited by 938
- 2020Encoding in Style: a StyleGAN Encoder for Image-to-Image Translationcited by 727
- 2022AdaFace: Quality Adaptive Margin for Face Recognitioncited by 391
- 2024LivePortrait: Efficient Portrait Animation with Stitching and Retargeting Controlcited by 206
- 2024PuLID: Pure and Lightning ID Customization via Contrastive Alignmentcited by 144
- 2023DCFace: Synthetic Face Generation with Dual Condition Diffusion Modelcited by 116
- 2021SynFace: Face Recognition with Synthetic Datacited by 106
- 2024Arc2Face: A Foundation Model for ID-Consistent Human Facescited by 101
- 2024EraseAnything: Enabling Concept Erasure in Rectified Flow Transformerscited by 95
- 2022DigiFace-1M: 1 Million Digital Face Images for Face Recognitioncited by 92
- 2023IDiff-Face: Synthetic-based Face Recognition through Fizzy Identity-Conditioned Diffusion Modelscited by 72
- 2020Face Morphing Attack Generation & Detection: A Comprehensive Surveycited by 64
- 2022SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Datacited by 63
- 2023GANDiffFace: Controllable Generation of Synthetic Datasets for Face Recognition with Realistic Variationscited by 49
- 2023SwinFace: A Multi-task Transformer for Face Recognition, Expression Recognition, Age Estimation and Attribute Estimationcited by 39
- 2022Unsupervised Face Recognition using Unlabeled Synthetic Datacited by 27
- 2024Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysiscited by 19
- 2021Concadia: Towards Image-Based Text Generation with a Purposecited by 15
- 2023Cross-Domain Image Captioning with Discriminative Finetuningcited by 14
- 2021Differential Morph Face Detection using Discriminative Wavelet Sub-bandscited by 13
- 2021Conditional Identity Disentanglement for Differential Face Morph Detectioncited by 12
- 2023Bias and Diversity in Synthetic-based Face Recognitioncited by 11
- 2024ONOT: a High-Quality ICAO-compliant Synthetic Mugshot Datasetcited by 10
- 2024ResEmoteNet: Bridging Accuracy and Loss Reduction in Facial Emotion Recognitioncited by 9
- 2024Facial Demorphing via Identity Preserving Image Decompositioncited by 8
- 2025Can Text-to-Image Generative Models Accurately Depict Age? A Comparative Study on Synthetic Portrait Generation and Age Estimationcited by 1
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