arXiv:2606. 28568v1 Announce Type: cross Abstract: Speech-driven 3D facial animation methods face significant challenges in simultaneously achieving high-fidelity motion and precise artistic control at production quality.
By Arthur Josi, Emeline Got, Abdallah Dib, Luiz Gustavo Hafemann, Rafael M. O. Cruz
EmbedTalk introduces per‑Gaussian embeddings to drive speech‑driven facial deformations in real‑time talking head synthesis, replacing traditional tri‑plane encodings. This approach improves rendering quality, lip synchronisation, and motion consistency compared to prior 3D Gaussian Splatting methods while producing more compact models that run at 60+ FPS on a laptop GPU. The technique demonstrates competitive performance against state‑of‑the‑art generative models.
By Arpita Saggar, Jonathan C. Darling, Duygu Sarikaya, David C. Hogg
arXiv:2608. 05218v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables fast, photorealistic talking-head rendering, yet accurate lip articulation remains elusive: mouth motion is often over-smoothed and may violate hard articulatory constraints such as bilabial closures, producing the notorious ``leaky mouth'' artifact.
By Ao Fu, Yi Zhou
Audio-driven talking head synthesis has achieved impressive progress in lip synchronization and visual quality, yet generating expressive emotional avatars with controllable intensity remains challenging, especially under real-time constraints. In this paper, we present GaussianEmoTalker, an audio-driven framework for real-time emotional talking head synthesis based on 3D Gaussian Splatting.
arXiv:2503. 14295v3 Announce Type: replace-cross Abstract: Recent advancements in audio-driven talking face generation have made great progress in lip synchronization.
By Baiqin Wang, Xiangyu Zhu, Fan Shen, Hao Xu, Zhen Lei
arXiv:2608.00663v2 Announce Type: replace
Abstract: Audio-driven emotional talking face generation aims to synthesize realistic videos with expressive facial dynamics. However, existing methods strug...
By Chenggong Hu, Shaoyin Ma, Yi Wang, Li Sun, Mingli Song, Jie Song
arXiv:2608.30951v1 Announce Type: new
Abstract: The rapid development of generative portrait models has raised growing concerns about privacy leakage and identity misuse. In particular, audio-driven...
By Rui-Qing Sun, Chen-Hao Cui, Hui-Yang Zhao, Tian Lan, Zhijing Wu, Xian-Ling Mao
arXiv:2608. 15110v1 Announce Type: cross Abstract: Emotional 3D talking head generation aims to synthesize expressive facial animations with accurate lip synchronization.
By Peng Jia, Li Dai, Zhen Xiao, Xueliang Liu, Jia Li
Emotional 3D talking head generation aims to synthesize expressive facial animations with accurate lip synchronization. However, existing methods often rely on discrete emotion categories, which fail...
arXiv:2602. 07106v2 Announce Type: replace-cross Abstract: Omni-modal large language models (OLLMs) aim to unify multimodal understanding and generation, yet extending them to jointly produce speech and 3D facial animation remains largely unexplored despite its importance for natural human-computer interaction.
By Haoyu Zhang, Zhipeng Li, Yiwen Guo, Tianshu Yu
arXiv:2606.00751v2 Announce Type: replace
Abstract: Visual Speech Recognition (VSR) aims to recognize speech from visual cues such as lip movements. Still, its performance is fundamentally limited by...
By Matthew Kit Khinn Teng, Haibo Zhang, Takeshi Saitoh
arXiv:2606. 30145v1 Announce Type: new Abstract: Natural face-to-face conversation requires real-time speech generation together with synchronized facial motion.
By Habin Lim, Jae-Ho Lee, Hah Min Lew, Ji-Su Kang, Gyeong-Moon Park