metadata
language:
- en
tags:
- webdataset
- audio
- motion
UniLS-Talk Dataset
To enable research on unified speaking and listening avatar generation, we curate and construct the UniLS-Talk Dataset, a large-scale collection of high-quality 3D facial motion data. We apply a carefully designed tracking pipeline to extract per-frame FLAME parameters, including expression coefficients, eye-gaze, jaw pose and head pose annotations. The dataset comprises two complementary parts:
- Paired conversational data sourced from the Seamless Interaction dataset, providing synchronized dual-speaker videos with natural turn-taking dynamics between speaking and listening.
- Unpaired multi-scenario data aggregated from CelebV, TalkingHead-1KH, TEDTalk, VFHQ, and other in-the-wild videos, covering diverse facial behaviors across identities and environments (news broadcasts, interviews, casual talking, etc.).
| Category | Source | Hours | Audio | Motion |
|---|---|---|---|---|
| Paired Conversational | Seamless Interaction Dataset | 657.5 h | ✅ | ✅ |
| Unpaired Multi-Scenario | Diverse identities and environments from in-the-wild videos | 546.5 h | ❌ | ✅ |
| Total | 1,204 h |
The paired conversational data is split into 622.5 hours for training, 4.8 hours for validation, and 30.2 hours for testing. All data includes FLAME expression parameters, jaw and head pose, and eye-gaze annotations at 25 fps.