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Charlie Hewitt

5 accepted papers

2025

DAViD: Data-efficient and Accurate Vision Models from Synthetic Data

ICCV 2025poster

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 of parameters, thus requiring extremely large datasets, expensive training regimes, and compute-intensive inference. In…

Cited by 0SourcePDFScholar
2025

GASP: Gaussian Avatars with Synthetic Priors

CVPR 2025poster

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 as Gaussian Avatars. Recent works have pushed the boundaries of quality and rendering efficiency but suffer from two main…

Cited by 0SourcePDFScholar
2025

VoluMe - Authentic 3D Video Calls from Live Gaussian Splat Prediction

ICCV 2025poster

Virtual 3D meetings offer the potential to enhance copresence, increase engagement and thus improve effectiveness of remote meetings compared to standard 2D video calls. However, representing people in 3D meetings remains a challenge; existing solutions achieve high quality by using complex hardware…

Cited by 0SourcePDFScholar
2022

3D Face Reconstruction with Dense Landmarks

ECCV 2022poster

"Landmarks often play a key role in face analysis, but many aspects of identity or expression cannot be represented by sparse landmarks alone. Thus, in order to reconstruct faces more accurately, landmarks are often combined with additional signals like depth images or techniques like differentiable…

2021

Fake It Till You Make It: Face Analysis in the Wild Using Synthetic Data Alone

ICCV 2021poster

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 training data with graphics, but the domain gap between real and synthetic data has remained a problem, especially for human…

Cited by 339PDFcodeScholar