arXiv Computer Vision
Oct 9

Fresco++: Frequency-Guided and Canonical-Consistent Optimization for Fine-Grained Head Avatar Modeling

Fresco++ is a unified optimization framework for fine‑grained, view‑consistent head avatar reconstruction. It uses a frequency‑guided curriculum that first stabilizes low‑frequency structures before adding high‑frequency constraints, and a Canonical Group Consensus that links local observations across viewpoints to enforce cross‑view consistency. The method incorporates geometric and visibility screening and aggregates multi‑view evidence in feature space, achieving stable optimization from coarse to fine details without extra rendering of auxiliary views.

By Shikun Zhang, Yong Li, Yiqun Wang, Qiuhong Ke, Cunjian Chen
arXiv Machine Learning
Oct 9

GHARP: Real-time Gaussian Head Animation from Large-scale Reconstruction Prior

GHARP is a two‑stage method that animates 3D human heads in real time using a large‑scale reconstruction prior. The first offline identity stage builds a compact Gaussian representation of a subject’s geometry and appearance, while the lightweight runtime animation stage predicts expression‑dependent residuals in a semantically structured latent space. A body alignment network further refines the animation by aligning body pose and clothing, enabling state‑of‑the‑art quality on the Ava‑256 benchmark with significantly faster performance and fewer Gaussians.

By Ali Benlalah, Sepehr Johari, Patricia Vitoria, Armin Kappeler, Artem Sevastopolsky, Alexander Jung, Gabriele Fanelli, Kevin Mader, Manuel Breitenstein, Claudia Pl\"uss, Jan R\"uegg, Simon Biland, Thomas Etterlin, Dmitry Kostiaev, Mathias Deschler, Brian Amberg, Sebastian Martin
arXiv Computer Vision
Sep 18

AGORA: Adversarial Generation Of Real-time Animatable 3D Gaussian Head Avatars

AGORA is a new framework that extends 3D Gaussian Splatting with a generative adversarial network to produce high‑fidelity, animatable 3D head avatars. It introduces a lightweight FLAME‑conditioned deformation branch that predicts per‑Gaussian residuals for identity‑preserving, fine‑grained expression control, and a dual‑discriminator training scheme that enforces expression fidelity. The system achieves real‑time inference at 250 FPS on a single GPU and, for the first time, CPU‑only animatable 3DGS avatar synthesis at ~9 FPS.

By Ramazan Fazylov, Sergey Zagoruyko, Aleksandr Parkin, Stamatis Lefkimmiatis, Ivan Laptev
arXiv AI
Jun 4

CounterFace: A Synthetic Face Dataset for Fine-Grained Counterfactual Evaluation of Face Recognition Systems

arXiv:2407. 13922v3 Announce Type: replace-cross Abstract: Face recognition (FR) systems are widely deployed in critical applications, making their reliability and robustness across diverse populations and conditions essential.

By Guruprasad Viswanathan Ramesh, Ashish Hooda, Shimaa Ahmed, Harrison J Rosenberg, Ramya Korlakai Vinayak, Kassem Fawaz