Hugging Face Trending Papers
emg2face: Expressive Facial Animation with High-Density Surface EMG
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arXiv Machine Learning
3d ago
emg2face: Expressive Facial Animation with High-Density Surface EMG
The paper presents emg2face, a system that uses high‑density surface electromyography (HD‑sEMG) to capture facial expressions without optical cameras, addressing issues of occlusion and privacy. It records 64 EMG channels with textile grids, synchronizes the data with video using analog audio bursts, and fits a high‑resolution parametric head model to 3D facial landmarks. A deep neural network then predicts blendshape parameters from the EMG signals, enabling real‑time facial animation on various characters.
arXiv Machine Learning
2d ago
GHARP: Real-time Gaussian Head Animation from Large-scale Reconstruction Prior
arXiv:2610.10945v1 Announce Type: cross Abstract: We present GHARP (Real-time Gaussian Head Animation from Large-scale Reconstruction Prior), a method that animates 3D human heads in real time from a...
arXiv Computer Vision
Sep 28
EmoZone-Talker: Regional Semantic Control of Audio-Driven 3DGS Talking Heads via Facial Action Units
arXiv:2606.15848v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has shown strong potential for high-fidelity talking head synthesis. However, enabling fine-grained, interpretable, an...
arXiv AI
Oct 2
One Basis to Animate Them All: Gaussian Blendshape Distillation for Real-Time Avatars
The paper introduces GALA, a distillation technique that replaces costly neural decoding in 3D Gaussian avatars with a shallow MLP predicting blendshape coefficients, enabling real‑time animation. By constructing a basis via block‑local PCA under a rendering‑aware metric, GALA achieves high fidelity while reducing memory usage. Experiments on three avatar models show up to three orders of magnitude lower CPU cost and frame rates up to 60fps on mobile devices.
arXiv Computer Vision
Sep 4
Occlusion-Robust Multimodal Emotion Recognition in VR via Fusion of Facial Images and EMG
The paper presents a method for emotion recognition in virtual reality where head‑mounted displays occlude the upper face. By fusing lower‑face video with electromyography (EMG) signals from the occluded upper face, the authors achieve a 51% macro‑F1 score across seven emotional categories, outperforming image‑only and EMG‑only baselines. A new synchronized multimodal dataset from 20 participants is introduced and will be shared under an ethical‑use agreement.
arXiv Computer Vision
Oct 1
MegaAvatar: Controllable Talking Avatar Generation
arXiv:2609.39273v1 Announce Type: new Abstract: This report presents \textbf{MegaAvatar}, a controllable talking avatar generation framework built on top of the Wan2.2-TI2V-5B model. Compared with pr...