Search Results for author:
Found 6 papers, 3 papers with code
MoSAR: Monocular Semi-Supervised Model for Avatar Reconstruction using Differentiable Shading
We also introduce a new dataset, named FFHQ-UV-Intrinsics, the first public dataset providing intrinsic face attributes at scale (diffuse, specular, ambient occlusion and translucency maps) for a total of 10k subjects.
Ranked #4 on
3D Face Reconstruction
on REALY
S2F2: Self-Supervised High Fidelity Face Reconstruction from Monocular Image
We present a novel face reconstruction method capable of reconstructing detailed face geometry, spatially varying face reflectance from a single monocular image.
Towards High Fidelity Monocular Face Reconstruction with Rich Reflectance using Self-supervised Learning and Ray Tracing
In this paper, we build our work on the aforementioned approaches and propose a new method that greatly improves reconstruction quality and robustness in general scenes.
Ranked #12 on
3D Face Reconstruction
on NoW Benchmark
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.
Practical Face Reconstruction via Differentiable Ray Tracing
The proposed method models scene illumination via a novel, parameterized virtual light stage, which in-conjunction with differentiable ray-tracing, introduces a coarse-to-fine optimization formulation for face reconstruction.
Face Reflectance and Geometry Modeling via Differentiable Ray Tracing
We present a novel strategy to automatically reconstruct 3D faces from monocular images with explicitly disentangled facial geometry (pose, identity and expression), reflectance (diffuse and specular albedo), and self-shadows.
