by America Ortiz | Dec 3, 2025 | Capture, Machine Learning, VFX
Implicit Bézier Motion Model for Precise Spatial and Temporal Control In this work, we introduce a new Implicit Bézier Motion Model (IBMM), which during training is exposed to all possible configurations of control points, enabling control at arbitrary timings. This...
by America Ortiz | Oct 26, 2025 | Capture, VFX, Visual Computing
Multimodal Conditional 3D Face Geometry Generation In this work, we present a new method for multimodal conditional 3D face geometry generation that allows user-friendly control over the output identity and expression via a number of different conditioning signals...
by America Ortiz | Oct 18, 2025 | Capture, VFX, Visual Computing
Joint Learning of Depth and Appearance for Portrait Images In this work, we propose to jointly learn the visual appearance and depth of faces simultaneously in a diffusion-based portrait image generator. Our method embraces the end-to-end diffusion paradigm and...
by America Ortiz | Oct 16, 2025 | Capture, VFX, Visual Computing
Monocular Facial Appearance Capture in the Wild In this work, we present a new method for reconstructing the appearance properties of human faces from a lightweight capture procedure in an unconstrained environment. October 16, 2025International Conference on Computer...
by America Ortiz | Jul 21, 2025 | Capture, Machine Learning, VFX
Synth2Track Editor for Efficient Match-Animation In this work, we developed new tools that significantly reduces the time required for complex shots, combining automation with human expertise to overcome the limitations of current markerless motion capture systems....
by America Ortiz | Jul 9, 2025 | Capture, VFX, Visual Computing
ScaffoldAvatar: High-Fidelity Gaussian Avatars with Patch Expressions In this work, we propose to couple locally-defined facial expressions with 3D Gaussian splatting to enable creating ultra-high fidelity, expressive and photorealistic head avatars. July 10,...
