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Found 20 papers, 6 papers with code
HERA: Hybrid Explicit Representation for Ultra-Realistic Head Avatars
We introduce a novel approach to creating ultra-realistic head avatars and rendering them in real time (\geq 30 fps at 2048 x1334 resolution).
One Shot, One Talk: Whole-body Talking Avatar from a Single Image
Building realistic and animatable avatars still requires minutes of multi-view or monocular self-rotating videos, and most methods lack precise control over gestures and expressions.
Portrait Video Editing Empowered by Multimodal Generative Priors
Extensive experiments demonstrate the temporal consistency, editing efficiency, and superior rendering quality of our method.
PICA: Physics-Integrated Clothed Avatar
We introduce PICA, a novel representation for high-fidelity animatable clothed human avatars with physics-accurate dynamics, even for loose clothing.
Hybrid Explicit Representation for Ultra-Realistic Head Avatars
We introduce a novel approach to creating ultra-realistic head avatars and rendering them in real-time (>30fps at $2048 \times 1334$ resolution).
FlashAvatar: High-fidelity Head Avatar with Efficient Gaussian Embedding
We propose FlashAvatar, a novel and lightweight 3D animatable avatar representation that could reconstruct a digital avatar from a short monocular video sequence in minutes and render high-fidelity photo-realistic images at 300FPS on a consumer-grade GPU.
CosAvatar: Consistent and Animatable Portrait Video Tuning with Text Prompt
Recently, text-guided digital portrait editing has attracted more and more attentions.
MetaHead: An Engine to Create Realistic Digital Head
Experiments validate that our controllable digital head engine achieves the state-of-the-art generation visual quality and reconstruction accuracy.
Reconstructing Personalized Semantic Facial NeRF Models From Monocular Video
We present a novel semantic model for human head defined with neural radiance field.
Prior-Guided Multi-View 3D Head Reconstruction
Extensive ablation studies and comparisons with state-of-the-art methods demonstrate that our method can generate high-fidelity 3D head geometries with the guidance of these priors.
StereoPIFu: Depth Aware Clothed Human Digitization via Stereo Vision
In this paper, we propose StereoPIFu, which integrates the geometric constraints of stereo vision with implicit function representation of PIFu, to recover the 3D shape of the clothed human from a pair of low-cost rectified images.
AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis
Generating high-fidelity talking head video by fitting with the input audio sequence is a challenging problem that receives considerable attentions recently.
Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model
To this end, we first build a dataset with various styles of 2D caricatures and their corresponding 3D shapes, and then build a parametric model on vertex based deformation space for 3D caricature face.
Lightweight Photometric Stereo for Facial Details Recovery
Recently, 3D face reconstruction from a single image has achieved great success with the help of deep learning and shape prior knowledge, but they often fail to produce accurate geometry details.
Semi-supervised 3D Face Reconstruction with Nonlinear Disentangled Representations
Moreover, the identity and expression representations are entangled in these models, which hurdles many facial editing applications.
3D Magic Mirror: Automatic Video to 3D Caricature Translation
Caricature is an abstraction of a real person which distorts or exaggerates certain features, but still retains a likeness.
3D Face From X: Learning Face Shape from Diverse Sources
Although 3D scanned data contain accurate geometric information of face shapes, the capture system is expensive and such datasets usually contain a small number of subjects.
Deep Face Feature for Face Alignment
The deep face feature (DFF) is trained using correspondence between face images rendered from different views.
CNN-based Real-time Dense Face Reconstruction with Inverse-rendered Photo-realistic Face Images
With the powerfulness of convolution neural networks (CNN), CNN based face reconstruction has recently shown promising performance in reconstructing detailed face shape from 2D face images.
Digital Makeup from Internet Images
Our algorithm is not restricted to one-to-one image color transfer and can make use of more than one target images to transfer the color in different parts in the source image.
