16 citations · 39 across the 10 of their papers we have counts for
11 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…
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…
BlendFields: Few-Shot Example-Driven Facial Modeling
Kacper Kania, Stephan J. Garbin, Andrea Tagliasacchi +5
Generating faithful visualizations of human faces requires capturing both coarse and fine-level details of the face geometry and appearance. Existing methods are either data-driven…
Photo-realistic 360 Head Avatars in the Wild
Stanislaw Szymanowicz, Virginia Estellers, Tadas Baltrusaitis +1
Delivering immersive, 3D experiences for human communication requires a method to obtain 360 degree photo-realistic avatars of humans. To make these experiences accessible to all,…
VolTeMorph: Realtime, Controllable and Generalisable Animation of Volumetric Representations
Stephan J. Garbin, Marek Kowalski, Virginia Estellers +5
The recent increase in popularity of volumetric representations for scene reconstruction and novel view synthesis has put renewed focus on animating volumetric content at high visu…
Fake It Till You Make It: Face analysis in the wild using synthetic data alone
Erroll Wood, Tadas Baltrušaitis, Charlie Hewitt +5
We demonstrate that it is possible to perform face-related computer vision in the wild using synthetic data alone. The community has long enjoyed the benefits of synthesizing train…
A high fidelity synthetic face framework for computer vision
Tadas Baltrusaitis, Erroll Wood, Virginia Estellers +6
Analysis of faces is one of the core applications of computer vision, with tasks ranging from landmark alignment, head pose estimation, expression recognition, and face recognition…
CONFIG: Controllable Neural Face Image Generation
Marek Kowalski, Stephan J. Garbin, Virginia Estellers +3
Our ability to sample realistic natural images, particularly faces, has advanced by leaps and bounds in recent years, yet our ability to exert fine-tuned control over the generativ…
Contrastive Learning for Lifted Networks
Christopher Zach, Virginia Estellers
In this work we address supervised learning of neural networks via lifted network formulations. Lifted networks are interesting because they allow training on massively parallel ha…
Compression for Smooth Shape Analysis
V. Estellers, F. R. Schmidt, D. Cremers
Most 3D shape analysis methods use triangular meshes to discretize both the shape and functions on it as piecewise linear functions. With this representation, shape analysis requir…
Enhanced Compressed Sensing Recovery with Level Set Normals
Virginia Estellers, Jean-Philippe Thiran, Xavier Bresson
We propose a compressive sensing algorithm that exploits geometric properties of images to recover images of high quality from few measurements. The image reconstruction is done by…