3DXTalker unifies identity modeling, lip synchronization, emotional expression, and head-pose dynamics in audio-driven 3D avatars via 2D-to-3D curation, amplitude/emotion audio cues, and a flow-matching transformer with prompt control.
Black, and Timo Bolkart
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
FFAvatar is a generalizable feed-forward framework that reconstructs high-quality animatable 3D Gaussian head avatars from few-shot unposed portrait images in seconds via Multi-View Query-Former and end-to-end FLAME prediction.
citing papers explorer
-
3DXTalker: Unifying Identity, Lip Sync, Emotion, and Spatial Dynamics in Expressive 3D Talking Avatars
3DXTalker unifies identity modeling, lip synchronization, emotional expression, and head-pose dynamics in audio-driven 3D avatars via 2D-to-3D curation, amplitude/emotion audio cues, and a flow-matching transformer with prompt control.
-
FFAvatar: Few-Shot, Feed-Forward, and Generalizable Avatar Reconstruction
FFAvatar is a generalizable feed-forward framework that reconstructs high-quality animatable 3D Gaussian head avatars from few-shot unposed portrait images in seconds via Multi-View Query-Former and end-to-end FLAME prediction.