9 papers
DP-RFT: Learning to Generate Synthetic Text via Differentially Private Reinforcement Fine-Tuning
Fangyuan Xu, Sihao Chen, Zinan Lin +13
Differentially private (DP) synthetic data generation plays a pivotal role in developing large language models (LLMs) on private data, where data owners cannot provide eyes-on acce…
DAViD: Data-efficient and Accurate Vision Models from Synthetic Data
Fatemeh Saleh, Sadegh Aliakbarian, Charlie Hewitt +5
The state of the art in human-centric computer vision achieves high accuracy and robustness across a diverse range of tasks. The most effective models in this domain have billions…
Total-Editing: Head Avatar with Editable Appearance, Motion, and Lighting
Yizhou Zhao, Chunjiang Liu, Haoyu Chen +6
Face reenactment and portrait relighting are essential tasks in portrait editing, yet they are typically addressed independently, without much synergy. Most face reenactment method…
Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model
Zinan Lin, Tadas Baltrusaitis, Wenyu Wang +1
Differentially private (DP) synthetic data, which closely resembles the original private data while maintaining strong privacy guarantees, has become a key tool for unlocking the v…
GASP: Gaussian Avatars with Synthetic Priors
Jack Saunders, Charlie Hewitt, Yanan Jian +8
Gaussian Splatting has changed the game for real-time photo-realistic rendering. One of the most popular applications of Gaussian Splatting is to create animatable avatars, known a…
SympCam: Remote Optical Measurement of Sympathetic Arousal
Björn Braun, Daniel McDuff, Tadas Baltrusaitis +3
Recent work has shown that a person's sympathetic arousal can be estimated from facial videos alone using basic signal processing. This opens up new possibilities in the field of t…