# Vec2Face: Unveil Human Faces from their Blackbox Features in Face Recognition

arXiv: https://arxiv.org/abs/2003.06958 · HTML: https://mlsanity.com/paper/2003.06958/

## Key facts

- Cited by 36 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Mar 2020.

## Built on by (most cited first, 30 of 36)

- [Text Embeddings Reveal (Almost) As Much As Text](https://mlsanity.com/paper/2310.06816/) (2023)
- [Arc2Face: A Foundation Model for ID-Consistent Human Faces](https://mlsanity.com/paper/2403.11641/) (2024)
- [Extracting Prompts by Inverting LLM Outputs](https://mlsanity.com/paper/2405.15012/) (2024)
- [The Right to Talk: An Audio-Visual Transformer Approach](https://mlsanity.com/paper/2108.03256/) (2021)
- [BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation](https://mlsanity.com/paper/2108.03267/) (2021)
- [Controllable Inversion of Black-Box Face Recognition Models via Diffusion](https://mlsanity.com/paper/2303.13006/) (2023)
- [FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition](https://mlsanity.com/paper/2112.12496/) (2021)
- [Cross-view Action Recognition Understanding From Exocentric to Egocentric Perspective](https://mlsanity.com/paper/2305.15699/) (2023)
- [OTAdapt: Optimal Transport-based Approach For Unsupervised Domain Adaptation](https://mlsanity.com/paper/2205.10738/) (2022)
- [CONDA: Continual Unsupervised Domain Adaptation Learning in Visual Perception for Self-Driving Cars](https://mlsanity.com/paper/2212.00621/) (2022)
- [Face Reconstruction from Face Embeddings using Adapter to a Face Foundation Model](https://mlsanity.com/paper/2411.03960/) (2024)
- [SlerpFace: Face Template Protection via Spherical Linear Interpolation](https://mlsanity.com/paper/2407.03043/) (2024)
- [Darker than Black-Box: Face Reconstruction from Similarity Queries](https://mlsanity.com/paper/2106.14290/) (2021)
- [Vec2Face-v2: Unveil Human Faces from their Blackbox Features via Attention-based Network in Face Recognition](https://mlsanity.com/paper/2209.04920/) (2022)
- [CROVIA: Seeing Drone Scenes from Car Perspective via Cross-View Adaptation](https://mlsanity.com/paper/2304.07199/) (2023)
- [Face Reconstruction Transfer Attack as Out-of-Distribution Generalization](https://mlsanity.com/paper/2407.02403/) (2024)
- [DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion](https://mlsanity.com/paper/2504.18015/) (2025)
- [IDFace: Face Template Protection for Efficient and Secure Identification](https://mlsanity.com/paper/2507.12050/) (2025)
- [Efficient Large-Scale Face Clustering Using an Online Mixture of Gaussians](https://mlsanity.com/paper/2103.17272/) (2021)
- [Assessing Privacy Risks from Feature Vector Reconstruction Attacks](https://mlsanity.com/paper/2202.05760/) (2022)
- [CoMaL: Conditional Maximum Likelihood Approach to Self-supervised Domain Adaptation in Long-tail Semantic Segmentation](https://mlsanity.com/paper/2304.07372/) (2023)
- [Approximating Optimal Morphing Attacks using Template Inversion](https://mlsanity.com/paper/2402.00695/) (2024)
- [Non-Adaptive Adversarial Face Generation](https://mlsanity.com/paper/2507.12107/) (2025)
- [Scores Know Bobs Voice: Speaker Impersonation Attack](https://mlsanity.com/paper/2603.02781/) (2026)
- [ID2image: Leakage of non-ID information into face descriptors and inversion from descriptors to images](https://mlsanity.com/paper/2304.07522/) (2023)
- [BIMA: Bijective Maximum Likelihood Learning Approach to Hallucination Prediction and Mitigation in Large Vision-Language Models](https://mlsanity.com/paper/2505.24649/) (2025)
- [Inverting Black-Box Face Recognition Systems via Zero-Order Optimization in Eigenface Space](https://mlsanity.com/paper/2506.09777/) (2025)
- [Constrained Particle Seeking: Solving Diffusion Inverse Problems with Just Forward Passes](https://mlsanity.com/paper/2603.01837/) (2026)
- [Revealing Unintentional Information Leakage in Low-Dimensional Facial Portrait Representations](https://mlsanity.com/paper/2503.09306/) (2025)
- [Cancelable Biometric Template Generation Using Random Feature Vector Transformations](https://mlsanity.com/paper/2503.15648/) (2025)

## Abstract (arXiv)

Unveiling face images of a subject given his/her high-level representations extracted from a blackbox Face Recognition engine is extremely challenging. It is because the limitations of accessible information from that engine including its structure and uninterpretable extracted features. This paper presents a novel generative structure with Bijective Metric Learning, namely Bijective Generative Adversarial Networks in a Distillation framework (DiBiGAN), for synthesizing faces of an identity given that person's features. In order to effectively address this problem, this work firstly introduces a bijective metric so that the distance measurement and metric learning process can be directly adopted in image domain for an image reconstruction task. Secondly, a distillation process is introduced to maximize the information exploited from the blackbox face recognition engine. Then a Feature-Conditional Generator Structure with Exponential Weighting Strategy is presented for a more robust generator that can synthesize realistic faces with ID preservation. Results on several benchmarking datasets including CelebA, LFW, AgeDB, CFP-FP against matching engines have demonstrated the effectiveness of DiBiGAN on both image realism and ID preservation properties.