arXiv (All)
open access
Personalizing Causal Audio-Driven Facial Motion via Dynamic Multi-modal Retrieval
Audio-driven facial animation is essential for immersive digital interaction, yet existing frameworks struggle to reconcile real-time streaming with high-fidelity personalization. Current methods either rely on latency-inducing audio look-ahead, or ask users to record scripted calibration sequences
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- FMReward: Aligning and Evaluating Audio-Driven 3D Facial Animation with Human Preferences#615270
- FMReward: Aligning and Evaluating Audio-Driven 3D Facial Animation with Human Preferences#614303
- Salt++: Context-Aligned Post-Training for Few-Step Streaming Multimodal Generation#1132196
- WeLike2Party! In-Context Motion Transfer for Multi-Human Image Animation#1132138
- PhyProbe: Rethinking Physical Consistency Evaluation in Generated Videos#1142978
Record · ID 1035475
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive