Real-time avatar animation speeds up on-device with a shared basis
A new method shows you can approximate complex avatar animation with a shared linear basis, enabling on-device speedups while keeping quality largely intact.
- Publication
- arXiv
- Stage
- Preprint
- What we read
- Summary of the paper
- Authors
- Ramazan Fazylov, Stamatis Lefkimmiatis, Ivan Laptev
- Universities and research institutions
- Not yet supplied in verified metadata; the Brief does not guess.
What they did and found
Researchers trained a neutral avatar and a small set of identity-specific tweaks, then used a tiny predictor to apply each tweak during animation. They tested on three avatar models, achieving noticeable CPU speedups while preserving most rendering quality, with some fine-detail errors.
Why it matters
This could let apps run smoother on phones, but gains vary by subject and motion; user tuning and awareness of limited identity detail may be needed.
In a hypothetical example, a creator could enroll a user once and run many animations quickly, using the small tweak set and predictor to guide motion.
Trade-offs include some loss of very fine detail and possible glitches in tricky poses, especially for identities not seen before.
What remains uncertain
Results depend on rendering choices and may be worse for unusual motions or unseen identities in some cases or settings.
Original sources · 1
- One Basis to Animate Them All: Gaussian Blendshape Distillation for Real-Time Avatars ↗arXiv · 2026-10-01
Check the original paper for its authors, methods, version and access terms.
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