Search Results for author:
Found 21 papers, 9 papers with code
X-Portrait: Expressive Portrait Animation with Hierarchical Motion Attention
We propose X-Portrait, an innovative conditional diffusion model tailored for generating expressive and temporally coherent portrait animation.
DREAM-Talk: Diffusion-based Realistic Emotional Audio-driven Method for Single Image Talking Face Generation
The generation of emotional talking faces from a single portrait image remains a significant challenge.
DiffPortrait3D: Controllable Diffusion for Zero-Shot Portrait View Synthesis
The rendering view is then manipulated with a novel conditional control module that interprets the camera pose by watching a condition image of a crossed subject from the same view.
MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion
In this work, we propose MagicPose, a diffusion-based model for 2D human pose and facial expression retargeting.
GETAvatar: Generative Textured Meshes for Animatable Human Avatars
We study the problem of 3D-aware full-body human generation, aiming at creating animatable human avatars with high-quality textures and geometries.
An interpretable deep learning method for bearing fault diagnosis
During the model evaluation process, the proposed approach retrieves prediction basis samples from the health library according to the similarity of the feature importance.
OmniAvatar: Geometry-Guided Controllable 3D Head Synthesis
We present OmniAvatar, a novel geometry-guided 3D head synthesis model trained from in-the-wild unstructured images that is capable of synthesizing diverse identity-preserved 3D heads with compelling dynamic details under full disentangled control over camera poses, facial expressions, head shapes, articulated neck and jaw poses.
AgileGAN3D: Few-Shot 3D Portrait Stylization by Augmented Transfer Learning
Capitalizing on the recent advancement of 3D-aware GAN models, we perform \emph{guided transfer learning} on a pretrained 3D GAN generator to produce multi-view-consistent stylized renderings.
PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360$^{\circ}$
We propose PanoHead, the first 3D-aware generative model that enables high-quality view-consistent image synthesis of full heads in $360^\circ$ with diverse appearance and detailed geometry using only in-the-wild unstructured images for training.
PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360deg
We propose PanoHead, the first 3D-aware generative model that enables high-quality view-consistent image synthesis of full heads in 360deg with diverse appearance and detailed geometry using only in-the-wild unstructured images for training.
AvatarGen: A 3D Generative Model for Animatable Human Avatars
Specifically, we decompose the generative 3D human synthesis into pose-guided mapping and canonical representation with predefined human pose and shape, such that the canonical representation can be explicitly driven to different poses and shapes with the guidance of a 3D parametric human model SMPL.
AvatarGen: a 3D Generative Model for Animatable Human Avatars
Unsupervised generation of clothed virtual humans with various appearance and animatable poses is important for creating 3D human avatars and other AR/VR applications.
Trajectory Optimization for Physics-Based Reconstruction of 3d Human Pose from Monocular Video
We focus on the task of estimating a physically plausible articulated human motion from monocular video.
Ranked #296 on
3D Human Pose Estimation
on Human3.6M
Feature Generation and Hypothesis Verification for Reliable Face Anti-Spoofing
However, the improvement is still limited by two issues: 1) It is difficult to perfectly map all faces to a shared feature space.
H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motion
This allows us to robustly fuse information from sparse views and generalize well beyond the poses or views observed in training.
imGHUM: Implicit Generative Models of 3D Human Shape and Articulated Pose
We present imGHUM, the first holistic generative model of 3D human shape and articulated pose, represented as a signed distance function.
Semi-supervised 3D Object Detection via Adaptive Pseudo-Labeling
Inspired by this, we propose a novel semi-supervised framework based on pseudo-labeling for outdoor 3D object detection tasks.
Understanding the effect of hyperparameter optimization on machine learning models for structure design problems
After HOpt, the training cost of ANN and RFR is increased more than that of the GPR and SVM.
GHUM & GHUML: Generative 3D Human Shape and Articulated Pose Models
We present a statistical, articulated 3D human shape modeling pipeline, within a fully trainable, modular, deep learning framework.
Weakly Supervised 3D Human Pose and Shape Reconstruction with Normalizing Flows
Monocular 3D human pose and shape estimation is challenging due to the many degrees of freedom of the human body and thedifficulty to acquire training data for large-scale supervised learning in complex visual scenes.
Ranked #53 on
3D Human Pose Estimation
on 3DPW
(PA-MPJPE metric)
Towards cross-platform automated rotation electron diffraction
A DigitalMicrograph script InsteaDMatic has been developed to facilitate rapid automated continuous rotation electron diffraction (cRED) data acquisition.
Materials Science
