# Is It Really You? Exploring Biometric Verification Scenarios in Photorealistic Talking-Head Avatar Videos

arXiv: https://arxiv.org/abs/2508.00748 · HTML: https://mlsanity.com/paper/2508.00748/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 38 references that are in the map.
- First posted on arXiv 1 Aug 2025.

## Builds on (most cited first, 24 of 24)

- [MOMENT: A Family of Open Time-series Foundation Models](https://mlsanity.com/paper/2402.03885/) (2024)
- [DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection](https://mlsanity.com/paper/2001.00179/) (2020)
- [Media Forensics and DeepFakes: an overview](https://mlsanity.com/paper/2001.06564/) (2020)
- [Generalizable and Animatable Gaussian Head Avatar](https://mlsanity.com/paper/2410.07971/) (2024)
- [Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs](https://mlsanity.com/paper/1907.06724/) (2019)
- [How Good is ChatGPT at Face Biometrics? A First Look into Recognition, Soft Biometrics, and Explainability](https://mlsanity.com/paper/2401.13641/) (2024)
- [Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitment](https://mlsanity.com/paper/2302.10908/) (2023)
- [RGBAvatar: Reduced Gaussian Blendshapes for Online Modeling of Head Avatars](https://mlsanity.com/paper/2503.12886/) (2025)
- [AvatarArtist: Open-Domain 4D Avatarization](https://mlsanity.com/paper/2503.19906/) (2025)
- [Exploring Transformers for Behavioural Biometrics: A Case Study in Gait Recognition](https://mlsanity.com/paper/2206.01441/) (2022)
- [BeCAPTCHA-Mouse: Synthetic Mouse Trajectories and Improved Bot Detection](https://mlsanity.com/paper/2005.00890/) (2020)
- [A multimodal dataset for understanding the impact of mobile phones on remote online virtual education](https://mlsanity.com/paper/2412.14195/) (2024)
- [Facial Expressions as a Vulnerability in Face Recognition](https://mlsanity.com/paper/2011.08809/) (2020)
- [SetMargin Loss applied to Deep Keystroke Biometrics with Circle Packing Interpretation](https://mlsanity.com/paper/2109.00938/) (2021)
- [Introduction to Presentation Attack Detection in Face Biometrics and Recent Advances](https://mlsanity.com/paper/2111.11794/) (2021)
- [Avatar Fingerprinting for Authorized Use of Synthetic Talking-Head Videos](https://mlsanity.com/paper/2305.03713/) (2023)
- [Biometrics and Behavior Analysis for Detecting Distractions in e-Learning](https://mlsanity.com/paper/2405.15434/) (2024)
- [Deepfake in the Metaverse: Security Implications for Virtual Gaming, Meetings, and Offices](https://mlsanity.com/paper/2303.14612/) (2023)
- [BeCAPTCHA: Detecting Human Behavior in Smartphone Interaction using Multiple Inbuilt Sensors](https://mlsanity.com/paper/2002.00918/) (2020)
- [SelfMAD: Enhancing Generalization and Robustness in Morphing Attack Detection via Self-Supervised Learning](https://mlsanity.com/paper/2504.05504/) (2025)
- [Benchmarking Graph Neural Networks for Document Layout Analysis in Public Affairs](https://mlsanity.com/paper/2505.14699/) (2025)
- [Type2Branch: Keystroke Biometrics based on a Dual-branch Architecture with Attention Mechanisms and Set2set Loss](https://mlsanity.com/paper/2405.01088/) (2024)
- [From Pixels to Words: Leveraging Explainability in Face Recognition through Interactive Natural Language Processing](https://mlsanity.com/paper/2409.16089/) (2024)
- [Comparison of Visual Trackers for Biomechanical Analysis of Running](https://mlsanity.com/paper/2505.04713/) (2025)

## Built on by (most cited first, 3 of 3)

- [Leveraging Avatar Fingerprinting: A Multi-Generator Photorealistic Talking-Head Public Database and Benchmark](https://mlsanity.com/paper/2603.26934/) (2026)
- [Is Visual Realism Enough? Evaluating Gait Biometric Fidelity in Generative AI Human Animation](https://mlsanity.com/paper/2512.19275/) (2025)
- [Micro-Expression-Aware Avatar Fingerprinting via Inter-Frame Feature Differencing](https://mlsanity.com/paper/2604.23247/) (2026)

## Abstract (arXiv)

Photorealistic talking-head avatars are becoming increasingly common in virtual meetings, gaming, and social platforms. These avatars allow for more immersive communication, but they also introduce serious security risks. One emerging threat is impersonation: an attacker can steal a user's avatar, preserving his appearance and voice, making it nearly impossible to detect its fraudulent usage by sight or sound alone. In this paper, we explore the challenge of biometric verification in such avatar-mediated scenarios. Our main question is whether an individual's facial motion patterns can serve as reliable behavioral biometrics to verify their identity when the avatar's visual appearance is a facsimile of its owner. To answer this question, we introduce a new dataset of realistic avatar videos created using a state-of-the-art one-shot avatar generation model, GAGAvatar, with genuine and impostor avatar videos. We also propose a lightweight, explainable spatio-temporal Graph Convolutional Network architecture with temporal attention pooling, that uses only facial landmarks to model dynamic facial gestures. Experimental results demonstrate that facial motion cues enable meaningful identity verification with AUC values approaching 80%. The proposed benchmark and biometric system are available for the research community in order to bring attention to the urgent need for more advanced behavioral biometric defenses in avatar-based communication systems.