Search Results for author:
Found 7 papers, 1 papers with code
Towards Reproducible Learning-based Compression
In this work, the irreproducibility issue is analyzed where deep learning is employed in compression systems while the encoding and decoding may be run on devices from different manufacturers.
WrappingNet: Mesh Autoencoder via Deep Sphere Deformation
There have been recent efforts to learn more meaningful representations via fixed length codewords from mesh data, since a mesh serves as a complete model of underlying 3D shape compared to a point cloud.
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.
FacialFilmroll: High-resolution multi-shot video editing
We present FacialFilmroll, a solution for spatially and temporally consistent editing of faces in one or multiple shots.
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
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.
