Search Results for author:
Found 11 papers, 5 papers with code
InvertAvatar: Incremental GAN Inversion for Generalized Head Avatars
While high fidelity and efficiency are central to the creation of digital head avatars, recent methods relying on 2D or 3D generative models often experience limitations such as shape distortion, expression inaccuracy, and identity flickering.
DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior
The score distillation from this 3D-aware diffusion prior provides view-consistent guidance for the scene.
HAvatar: High-fidelity Head Avatar via Facial Model Conditioned Neural Radiance Field
The problem of modeling an animatable 3D human head avatar under light-weight setups is of significant importance but has not been well solved.
Control4D: Efficient 4D Portrait Editing with Text
We introduce Control4D, an innovative framework for editing dynamic 4D portraits using text instructions.
StyleAvatar: Real-time Photo-realistic Portrait Avatar from a Single Video
Results and experiments demonstrate the superiority of our method in terms of image quality, full portrait video generation, and real-time re-animation compared to existing facial reenactment methods.
High-fidelity Facial Avatar Reconstruction from Monocular Video with Generative Priors
Compared with existing works, we obtain superior novel view synthesis results and faithfully face reenactment performance.
Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars
We propose a novel 3D GAN framework for unsupervised learning of generative, high-quality and 3D-consistent facial avatars from unstructured 2D images.
DiffuStereo: High Quality Human Reconstruction via Diffusion-based Stereo Using Sparse Cameras
At its core is a novel diffusion-based stereo module, which introduces diffusion models, a type of powerful generative models, into the iterative stereo matching network.
IDE-3D: Interactive Disentangled Editing for High-Resolution 3D-aware Portrait Synthesis
Existing 3D-aware facial generation methods face a dilemma in quality versus editability: they either generate editable results in low resolution or high-quality ones with no editing flexibility.
FENeRF: Face Editing in Neural Radiance Fields
2D GANs can generate high fidelity portraits but with low view consistency.
BusTime: Which is the Right Prediction Model for My Bus Arrival Time?
With the rise of big data technologies, many smart transportation applications have been rapidly developed in recent years including bus arrival time predictions.
