Search Results for author:
Found 8 papers, 1 papers with code
AvatarStudio: Text-driven Editing of 3D Dynamic Human Head Avatars
Our method edits the full head in a canonical space, and then propagates these edits to remaining time steps via a pretrained deformation network.
GVP: Generative Volumetric Primitives
Advances in 3D-aware generative models have pushed the boundary of image synthesis with explicit camera control.
HQ3DAvatar: High Quality Controllable 3D Head Avatar
This paper presents a novel approach to building highly photorealistic digital head avatars.
State of the Art in Dense Monocular Non-Rigid 3D Reconstruction
3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics.
Disentangled3D: Learning a 3D Generative Model with Disentangled Geometry and Appearance from Monocular Images
Our model can disentangle the geometry and appearance variations in the scene, i. e., we can independently sample from the geometry and appearance spaces of the generative model.
Efficient and Differentiable Shadow Computation for Inverse Problems
Differentiable rendering has received increasing interest for image-based inverse problems.
PhotoApp: Photorealistic Appearance Editing of Head Portraits
We present an approach for high-quality intuitive editing of the camera viewpoint and scene illumination in a portrait image.
Learning Complete 3D Morphable Face Models from Images and Videos
Our network design and loss functions ensure a disentangled parameterization of not only identity and albedo, but also, for the first time, an expression basis.
