Face Reconstruction
72 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
Most implemented papers
Learning an Animatable Detailed 3D Face Model from In-The-Wild Images
Some methods produce faces that cannot be realistically animated because they do not model how wrinkles vary with expression.
HairMapper: Removing Hair From Portraits Using GANs
Removing hair from portrait images is challenging due to the complex occlusions between hair and face, as well as the lack of paired portrait data with/without hair.
Perspective Reconstruction of Human Faces by Joint Mesh and Landmark Regression
Even though 3D face reconstruction has achieved impressive progress, most orthogonal projection-based face reconstruction methods can not achieve accurate and consistent reconstruction results when the face is very close to the camera due to the distortion under the perspective projection.
FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models
The ability to create high-quality 3D faces from a single image has become increasingly important with wide applications in video conferencing, AR/VR, and advanced video editing in movie industries.
TIFace: Improving Facial Reconstruction through Tensorial Radiance Fields and Implicit Surfaces
This report describes the solution that secured the first place in the "View Synthesis Challenge for Human Heads (VSCHH)" at the ICCV 2023 workshop.
Multilinear Wavelets: A Statistical Shape Space for Human Faces
We show that in comparison to a global multilinear model, our model better preserves fine detail and is computationally faster, while in comparison to a localized PCA model, our model better handles variation in expression, is faster, and allows us to fix identity parameters for a given subject.
Review of Statistical Shape Spaces for 3D Data with ComparativeAnalysis for Human Faces
Due to the wide avail-ability of databases of high-quality data, we use the human face as the specific shape we wish to extract from corrupted data.
Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression
Our CNN works with just a single 2D facial image, does not require accurate alignment nor establishes dense correspondence between images, works for arbitrary facial poses and expressions, and can be used to reconstruct the whole 3D facial geometry (including the non-visible parts of the face) bypassing the construction (during training) and fitting (during testing) of a 3D Morphable Model.
Extreme 3D Face Reconstruction: Seeing Through Occlusions
Motivated by the concept of bump mapping, we propose a layered approach which decouples estimation of a global shape from its mid-level details (e. g., wrinkles).
Pixel-Level Alignment of Facial Images for High Accuracy Recognition Using Ensemble of Patches
The geometry alignment is performed pixel-wise, i. e., every pixel of the face is corresponded to a pixel of the reference face.