Face Reconstruction
74 papers with code • 0 benchmarks • 3 datasets
Face reconstruction is the task of recovering the facial geometry of a face from an image.
( Image credit: Microsoft Deep3DFaceReconstruction )
Benchmarks
These leaderboards are used to track progress in Face Reconstruction
FaceWarehouse
FaceScape
ICT-3DHP
Latest papers with no code
Learning Topology Uniformed Face Mesh by Volume Rendering for Multi-view Reconstruction
Our goal is to leverage the superiority of neural volume rendering into multi-view reconstruction of face mesh with consistent topology.
3D Facial Expressions through Analysis-by-Neural-Synthesis
Instead, SMIRK replaces the differentiable rendering with a neural rendering module that, given the rendered predicted mesh geometry, and sparsely sampled pixels of the input image, generates a face image.
SplatFace: Gaussian Splat Face Reconstruction Leveraging an Optimizable Surface
Our method is designed to simultaneously deliver both high-quality novel view rendering and accurate 3D mesh reconstructions.
Makeup Prior Models for 3D Facial Makeup Estimation and Applications
Although there is a trade-off between the two models, both are applicable to 3D facial makeup estimation and related applications.
Skull-to-Face: Anatomy-Guided 3D Facial Reconstruction and Editing
Existing methods for automated facial reconstruction yield inaccurate results, suffering from the non-determinative nature of the problem that a skull with a sparse set of tissue depth cannot fully determine the skinned face.
VRMM: A Volumetric Relightable Morphable Head Model
In this paper, we introduce the Volumetric Relightable Morphable Model (VRMM), a novel volumetric and parametric facial prior for 3D face modeling.
Exploring 3D-aware Lifespan Face Aging via Disentangled Shape-Texture Representations
Existing face aging methods often focus on modeling either texture aging or using an entangled shape-texture representation to achieve face aging.
Robust Geometry and Reflectance Disentanglement for 3D Face Reconstruction from Sparse-view Images
This paper presents a novel two-stage approach for reconstructing human faces from sparse-view images, a task made challenging by the unique geometry and complex skin reflectance of each individual.
MonoNPHM: Dynamic Head Reconstruction from Monocular Videos
We present Monocular Neural Parametric Head Models (MonoNPHM) for dynamic 3D head reconstructions from monocular RGB videos.
FitDiff: Robust monocular 3D facial shape and reflectance estimation using Diffusion Models
This model accurately generates relightable facial avatars, utilizing an identity embedding extracted from an "in-the-wild" 2D facial image.
