Face Reconstruction
75 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
Latest papers
3D Face Reconstruction Using A Spectral-Based Graph Convolution Encoder
To overcome this limitation and enhance the reconstruction of 3D structural features, we propose an innovative approach that integrates existing 2D features with 3D features to guide the model learning process.
Eye Motion Matters for 3D Face Reconstruction
Recent advances in single-image 3D face reconstruction have shown remarkable progress in various applications.
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.
ImFace++: A Sophisticated Nonlinear 3D Morphable Face Model with Implicit Neural Representations
Accurate representations of 3D faces are of paramount importance in various computer vision and graphics applications.
3D Face Reconstruction with the Geometric Guidance of Facial Part Segmentation
In this paper, we fully utilize the facial part segmentation geometry by introducing Part Re-projection Distance Loss (PRDL).
Unveiling the Two-Faced Truth: Disentangling Morphed Identities for Face Morphing Detection
Over time they have become simpler to perform and more realistic, as such, the usage of deep learning systems to detect these attacks has grown.
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.
Face Animation with an Attribute-Guided Diffusion Model
Face animation has achieved much progress in computer vision.
3D Facial Imperfection Regeneration: Deep learning approach and 3D printing prototypes
This study explores the potential of a fully convolutional mesh autoencoder model for regenerating 3D nature faces with the presence of imperfect areas.
A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images
Meanwhile, 3D priors of facial details are incorporated to enhance the accuracy and authenticity of the reconstruction results.