Face recognition and analysis

Neueste Paper

• One Basis to Animate Them All: Gaussian Blendshape Distillation for Real-Time Avatars

  Ramazan Fazylov, Stamatis Lefkimmiatis, Ivan Laptev · 2. Oktober 2026

  3D Gaussian avatars support fast rendering, however, their real-time animation is often challenged by the costly neural inference. We address this bottleneck and show that the animation of pretrained avatar models can be closely approximated by a linear combination of identity-independent blendshape…

• MegaAvatar: Controllable Talking Avatar Generation

  Junyao Gao, Sibo Liu, Weidong Zhang, Cairong Zhao, Jun Zhang · 1. Oktober 2026

  This report presents \textbf{MegaAvatar}, a controllable talking avatar generation framework built on top of the Wan2.2-TI2V-5B model. Compared with previous talking-avatar methods that mainly rely on audio or reference-image conditioning, we introduce additional SMPL-X-derived 3D guidance, enabling…

• Learning Semantic Inpainting for Animatable Gaussian Head Avatars

  Pilseo Park, Fizza Rubab, Yiying Tong · 1. Oktober 2026

  We present SInGA, a novel method for learning Semantic Inpainting for animatable Gaussian head Avatars from a single image. Existing avatar approaches often rely on multi-view observations and lack effective handling of unobserved regions in single-view settings, limiting their applicability in such…

• A Comparative Transfer-Learning Study of CNN Backbones for Partial Face Recognition on the SoF Dataset

  Ahmed Kubba, Ali Alsalama, Abdelrahman Abdalla, Qassim Nasir, Manar Abu Talib · 29. September 2026

  Face recognition is widely deployed in surveillance, access control, and forensic workflows, yet accuracy degrades sharply once the face is occluded by accessories, foreground objects, or the frame edge. Because most faces in the wild are partial, robust partial face recognition (PFR) remains open. …

• Seeing Speech: Learning Visible Articulatory Dynamics for Speech-Driven 3D Facial Animation

  Hyung Kyu Kim, Byungchan Hwang, Hak Gu Kim · 28. September 2026

  Recent progress in speech-driven 3D facial animation has improved vertex-level reconstruction quality, but speech-consistent visible articulation remains difficult. This is because speech production follows structured and constrained articulators' coordination and the mapping from acoustics to motio…

• Long-Tail Adaptive Flow Matching with Explicit Conditional Consistency Guidance for Precise Multimodal Face Synthesis

  Yushe Cao, Xuechao Zou, Xing Xi, Dianxi Shi, Chun Yu, Junliang Xing · 25. September 2026

  Although diffusion-based methods have substantially improved the controllability of multimodal face synthesis, their semantic alignment remains suboptimal because most existing approaches rely on implicit latent-space objectives to model the relationship between denoising variables and multimodal co…

• Pose Adaptive Dynamic FiLM Modulation for Visual Speech Recognition

  Matthew Kit Khinn Teng, Haibo Zhang, Takeshi Saitoh · 25. September 2026

  Head-pose variation introduces substantial appearance transformations in visual speech recognition (VSR), making pose-aware feature modulation desirable. However, performance degradation and unwanted feature interactions may result from using numerous Feature-wise Linear Modulation (FiLM) circuits w…

• Damnatio Memoriae: Adversarially and Selectively Forgetting Identities in the Embedding Space of Face Recognition Models

  \"Unsal \"Ozt\"urk, Vedrana Krivoku\'ca Hahn, Sushil Bhattacharjee, S\'ebastien Marcel · 24. September 2026

  A face recognition model links two images of a person recorded on separate occasions when their embedding similarity exceeds an operating threshold. We consider making chosen identities unlinkable across separate occasions while the model remains in service for the rest of the population. Deleting t…

• HYDRO: Towards Non-Reversible Face De-Identification Using a High-Fidelity Hybrid Diffusion and Target-Oriented Approach

  Felix Rosberg, Vitomir \v{S}truc, Cristofer Englund, Eren Erdal Aksoy, Fernando Alonso-Fernandez · 24. September 2026

  Target-oriented face de-identification models aim to anonymize the identity of a target individual across different images or video frames, such that the target can no longer be reliably recognized, while maintaining key characteristics of the visual data. Such models commonly leverage generative en…

• Relightable 3D Avatar Reconstruction with Semantic-Adaptive Motion-Illumination Responses

  Jiankuo Zhao, Xiangyu Zhu, Jijie Li, Baiqin Wang, Shukai Chen, Zhen Lei · 22. September 2026

  Reconstructing expressive and relightable 3D head avatars from monocular videos remains challenging in computer vision, as it requires accurate modeling of both non-rigid facial motion and illumination-dependent appearance. Existing Gaussian avatar methods commonly rely on globally coupled represent…

• Towards Robust Classroom Attendance: A Comprehensive Evaluation of Face Detection and Recognition Models

  Himani Trivedi, Hiren Patel, Ridham Patel, Krutika Patel, Nancy Patel · 22. September 2026

  Manual attendance methods, such as paper or register-based systems, take a lot of time, can lead to errors, and are easy to falsify. Face recognition is more reliable, but it frequently struggles in classrooms because lighting and other conditions can vary. Face recognition datasets are designed for…

• Complementary rPPG-Derived and Lip-Region Frequency Cues for Talking-Face Deepfake Detection

  Othmane Harraq, Tamer Aldwairi · 22. September 2026

  Talking-face (TF) deepfakes are detected unevenly by rPPG-based methods across generators. We study two lightweight visual-only cues, rPPG-derived waveforms extracted by RhythmFormer and lip-region discrete cosine transform (DCT) coefficients, on the seven TF methods of Celeb-DF++ under a subject-in…

• KoUniTalk: A Lightweight Articulation-Centered Korean-English 3D Talking Face Benchmark

  Hyunjung Chung, Unsang Park · 18. September 2026

  High-quality 3D talking face datasets remain largely English- centric, and Korean 3D facial motion data are difficult to combine with standard English benchmarks because of differences in mesh topology, spatial scale, coordinate system, and temporal sampling. We present KoUniTalk, a lightweight arti…

• FAHCD-Net: Frequency-Adaptive Heatmap-Conditional Diffusion Networks for Robust Facial Landmark Detection

  Jun Wan, Jiwei Hu, Shengkai Hu, Qilu Zhu · 16. September 2026

  Facial Landmark Detection(FLD) is a crucial task in various applications and has achieved significant advancements in recent years. However, current FLD methods still struggle under challenging conditions, where facial structural variations, information loss, and noise interference severely compromi…

• DenseFace: Bias Mitigation in Face Recognition via Density-Aware Probabilistic Matching

  Mansur Bultygov, Vadim Seliutin, Dmitry Nekhaev, Ivan Laptev · 16. September 2026

  Despite steady progress in face recognition, current face recognition models still suffer from significant demographic biases. While approaches for bias mitigation have been proposed, existing methods often impose constraints on the training procedure and result in the degradation of recognition acc…

• BEACON: Behavior and Appearance Control for Subject-Specific Video Generation

  Pokrzywa Baptiste, Nabyl Quignon, Yara Bahram, Muhammad Osama Zeeshan, Antitza Dantcheva, Eric Granger · 15. September 2026

  Generating human-centric videos that preserve both visual identity and person-specific expressive behavior remains a fundamental challenge. In addition to reproducing appearance, a model must replicate the facial behaviors that characterize how a subject expresses emotion over time. However, most st…

• MGAvatar: Mesh-Bound Gaussians for Head Avatar Geometry and Appearance Modeling

  Lei Shi, Sen Peng, Zhiyang Deng, Zhonggui Chen, Xiaohu Guo, Baorong Yang, Xiao Dong · 14. September 2026

  Accurate head modeling requires a stable yet expressive geometric representation. Existing Gaussian-based head avatars commonly rely on parametric templates (e.g., FLAME) for Gaussian initialization and deformation, but these templates lack personalized priors and struggle to represent structures su…

• SynThermFace: Amplifying Limited Paired Data for Visible-Thermal Face Recognition via Synthetic Data Generation

  Anjith George, Adam Unal, Sebastien Marcel · 10. September 2026

  Face recognition (FR) is a widely used modality for biometric authentication, but conventional models rely on visible-spectrum imagery and degrade when high-quality RGB images cannot be captured. Cross-spectral face recognition addresses this limitation by matching visible images with other modaliti…

• FreqFLD: Towards All-in-One Facial Landmark Detection via Frequency Modulation

  Shun Ren, Kaijie Jin, Shengkai Hu, Beihang Song, Hang Sun, Wenwen Min, Youfa Liu, Jun Wan · 10. September 2026

  Recent progress in deep learning has significantly advanced facial landmark detection. However, most existing methods process features in a spatial-domain manner under a dataset-specific training paradigm, which overlooks the fact that facial landmark detection is inherently geometry-driven and sens…

• Low-Quality Face Recognition using Center Aligned Representations and Local Margin Constraints

  Vedat Can Dilaver, Benjamin S. Riggan · 2. September 2026

  Low-quality face recognition (LQFR) remains challenging due to the difficulty of matching degraded query (probe) images against low-quality (LQ) enrollment (gallery) imagery and the scarcity of training data for large-scale models. While recent face recognition (FR) models perform well on high-quali…

• Unmasking Face Embeddings: Reading, Rendering and Naming with Foundation Models

  Fizza Rubab, Yiying Tong, Arun Ross · 2. September 2026

  Modern face recognition (FR) owes much of its success to deep neural networks that learn to extract compact identity embeddings from face images. These models are typically trained for identity discrimination, producing embeddings that are highly effective for biometric matching but largely opaque t…

• Revisiting Face Recognition for Monozygotic Twins: The Celeb Twins Test Set

  Michael Zang, Haiyu Wu, Mrinal Sharma, Kevin W. Bowyer · 2. September 2026

  Past literature on face recognition for monozygotic (("identical") twins points to facial marks and mirror asymmetry as possible directions for improved accuracy of twins recognition. The Celeb Twins Test Set (CTTS) contains web-scraped image pairs for 80 sets of celebrity twins. It is the only twin…

• ClassVision: AI-Powered Classroom Attendance System

  Ankit Kumar Aggarwal, Veerabhadra Rao Marellapudi, Ovadia Sutton, Youshan Zhang · 28. August 2026

  Students and working professionals have to go through the attendance process every day. Traditional methods of marking attendance using pen and paper or online platforms are human-intensive and time-consuming. To address the challenges in manual attendance processes, this research explores the use o…

• Unlocking the power of partnership: How humans and machines can work together to improve face recognition

  P. Jonathon Phillips (Information Access Division, National Institute of Standards and Technology, Gaithersburg, MD), Geraldine Jeckeln (School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX), Amy N. Yates (Information Access Division, National Institute of Standards and Technology, Gaithersburg, MD), Carina A. Hahn (Information Access Division, National Institute of Standards and Technology, Gaithersburg, MD), Peter C. Fontana (Information Access Division, National Institute of Standards and Technology, Gaithersburg, MD), Alice J. O'Toole (School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX) · 26. August 2026

  Human review of consequential decisions by face recognition algorithms creates a collaborative human-machine system. We establish the circumstances under which combining human and machine face identification decisions improves accuracy. Using data from expert and non-expert face identifiers, we show…

• Beauty is in the ELBO of the Beholder: A Variational Account of Processing Fluency in Face Perception

  Francisco M. L\'opez, Jochen Triesch · 26. August 2026

  Facial attractiveness has been linked to statistical regularities such as symmetry and averageness, suggesting that beauty may depend on the ease with which a face is perceived. We empirically test this hypothesis by training variational autoencoders on four face datasets without attractiveness supe…