Search Results for author:
Found 18 papers, 5 papers with code
Eyeglasses 3D shape reconstruction from a single face image
A complete 3D face reconstruction requires to explicitly model the eyeglasses on the face, which is less investigated in the literature.
CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning
Learning latent motion from Internet videos is crucial for building generalist robots.
3D Gaussian Head Avatars with Expressive Dynamic Appearances by Compact Tensorial Representations
Recent studies have combined 3D Gaussian and 3D Morphable Models (3DMM) to construct high-quality 3D head avatars.
Textual Decomposition Then Sub-motion-space Scattering for Open-Vocabulary Motion Generation
For Textual Decomposition, we design a fine-grained description conversion algorithm, and combine it with the generalization ability of a large language model to convert any given motion text into atomic texts.
SPA: 3D Spatial-Awareness Enables Effective Embodied Representation
The results are compelling: SPA consistently outperforms more than 10 state-of-the-art representation methods, including those specifically designed for embodied AI, vision-centric tasks, and multi-modal applications, while using less training data.
ID-Sculpt: ID-aware 3D Head Generation from Single In-the-wild Portrait Image
We then use the canny map, ID features of the portrait image, and a pre-trained text-to-normal/depth diffusion model to generate ID-aware geometry supervision, and 3D-GAN inversion is employed to generate ID-aware geometry initialization.
DGRC: An Effective Fine-tuning Framework for Distractor Generation in Chinese Multi-choice Reading Comprehension
When evaluating a learner's knowledge proficiency, the multiple-choice question is an efficient and widely used format in standardized tests.
MotionMaster: Training-free Camera Motion Transfer For Video Generation
Furthermore, we propose a few-shot camera motion disentanglement method to extract the common camera motion from multiple videos with similar camera motions, which employs a window-based clustering technique to extract the common features in temporal attention maps of multiple videos.
Learning Topology Uniformed Face Mesh by Volume Rendering for Multi-view Reconstruction
Our goal is to leverage the superiority of neural volume rendering into multi-view reconstruction of face mesh with consistent topology.
Learning-based Multi-continuum Model for Multiscale Flow Problems
Multiscale problems can usually be approximated through numerical homogenization by an equation with some effective parameters that can capture the macroscopic behavior of the original system on the coarse grid to speed up the simulation.
Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning
These outcomes suggest that the 3D point cloud is a valuable observation modality for intricate robotic tasks.
AMS-Net: Adaptive Multiscale Sparse Neural Network with Interpretable Basis Expansion for Multiphase Flow Problems
In this work, we propose an adaptive sparse learning algorithm that can be applied to learn the physical processes and obtain a sparse representation of the solution given a large snapshot space.
An adaptive Hessian approximated stochastic gradient MCMC method
The bias introduced by stochastic approximation is controllable and can be analyzed theoretically.
Bayesian Sparse learning with preconditioned stochastic gradient MCMC and its applications
The algorithm utilizes a set of spike-and-slab priors for the parameters in the deep neural network.
XCloud: Design and Implementation of AI Cloud Platform with RESTful API Service
In recent years, artificial intelligence (AI) has aroused much attention among both industrial and academic areas.
Distributed, Parallel, and Cluster Computing
Efficient Deep Learning Techniques for Multiphase Flow Simulation in Heterogeneous Porous Media
In particular, for the flow problem, we design a network with convolutional and locally connected layers to perform model reductions.
Numerical Analysis Numerical Analysis
Data-driven Approach for Quality Evaluation on Knowledge Sharing Platform
In recent years, voice knowledge sharing and question answering (Q&A) platforms have attracted much attention, which greatly facilitate the knowledge acquisition for people.
Deep Multiscale Model Learning
Numerical results show that using deep learning and multiscale models, we can improve the forward models, which are conditioned to the available data.
