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Face Reconstruction

Face reconstruction is the task of recovering the facial geometry of a face from an image.

( Image credit: Microsoft Deep3DFaceReconstruction )

Papers

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Showing 101–125 of 259 papers

TitleStatusHype
Accurate 3D Face Reconstruction with Facial Component Tokens—0
GAN2X: Non-Lambertian Inverse Rendering of Image GANs—0
Continuous Landmark Detection With 3D Queries—0
FreeAvatar: Robust 3D Facial Animation Transfer by Learning an Expression Foundation Model—0
Consistent and symmetry preserving data-driven interface reconstruction for the level-set method—0
3D-TalkEmo: Learning to Synthesize 3D Emotional Talking Head—0
3D Face Reconstruction: the Road to Forensics—0
Generative Adversarial Network-based Synthesis of Visible Faces from Polarimetric Thermal Faces—0
Generative Face Parsing Map Guided 3D Face Reconstruction Under Occluded Scenes—0
Generative Landmarks Guided Eyeglasses Removal 3D Face Reconstruction—0
FitDiff: Robust monocular 3D facial shape and reflectance estimation using Diffusion Models—0
CNN-based Real-time Dense Face Reconstruction with Inverse-rendered Photo-realistic Face Images—0
FEAFA: A Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation—0
B-spline Shape from Motion & Shading: An Automatic Free-form Surface Modeling for Face Reconstruction—0
Fast and Robust Face-to-Parameter Translation for Game Character Auto-Creation—0
Fast 3D Reconstruction of Faces With Glasses—0
High-Fidelity Facial Albedo Estimation via Texture Quantization—0
High-Quality 3D Face Reconstruction with Affine Convolutional Networks—0
Identity-Preserving Pose-Robust Face Hallucination Through Face Subspace Prior—0
3D human tongue reconstruction from single "in-the-wild" images—0
Implicit Neural Deformation for Sparse-View Face Reconstruction—0
Improving Fairness in Facial Albedo Estimation via Visual-Textual Cues—0
3D face reconstruction from single image with generative adversarial networks—0
InverseFaceNet: Deep Monocular Inverse Face Rendering—0
3D Dense Face Alignment via Graph Convolution Networks—0
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