research
∙
08/15/2023
StyleDiffusion: Controllable Disentangled Style Transfer via Diffusion Models
Content and style (C-S) disentanglement is a fundamental problem and cri...
share
research
∙
05/26/2023
Joint Optimization of Triangle Mesh, Material, and Light from Neural Fields with Neural Radiance Cache
Traditional inverse rendering techniques are based on textured meshes, w...
research
∙
04/26/2023
VGOS: Voxel Grid Optimization for View Synthesis from Sparse Inputs
Neural Radiance Fields (NeRF) has shown great success in novel view synt...
research
∙
03/23/2023
Generative Image Inpainting with Segmentation Confusion Adversarial Training and Contrastive Learning
This paper presents a new adversarial training framework for image inpai...
research
∙
11/28/2022
MicroAST: Towards Super-Fast Ultra-Resolution Arbitrary Style Transfer
Arbitrary style transfer (AST) transfers arbitrary artistic styles onto ...
research
∙
08/27/2022
AesUST: Towards Aesthetic-Enhanced Universal Style Transfer
Recent studies have shown remarkable success in universal style transfer...
research
∙
03/01/2022
E-LMC: Extended Linear Model of Coregionalization for Predictions of Spatial Fields
Physical simulations based on partial differential equations typically g...
research
∙
12/06/2021
Texture Reformer: Towards Fast and Universal Interactive Texture Transfer
In this paper, we present the texture reformer, a fast and universal neu...
research
∙
01/16/2021
Diversified Patch-based Style Transfer with Shifted Style Normalization
Gram-based and patch-based approaches are two important research lines o...
research
∙
08/08/2020
Multimodal Image-to-Image Translation via Mutual Information Estimation and Maximization
In this paper, we present a novel framework that can achieve multimodal ...
research
∙
07/06/2020
Multi-Fidelity Bayesian Optimization via Deep Neural Networks
Bayesian optimization (BO) is a popular framework to optimize black-box ...
research
∙
06/08/2020
Physics Regularized Gaussian Processes
We consider incorporating incomplete physics knowledge, expressed as dif...
research
∙
06/08/2020
Multi-Fidelity High-Order Gaussian Processes for Physical Simulation
The key task of physical simulation is to solve partial differential equ...
research
∙
03/25/2020
Scalable Variational Gaussian Process Regression Networks
Gaussian process regression networks (GPRN) are powerful Bayesian models...
research
∙
10/16/2019
Deep Coregionalization for the Emulation of Spatial-Temporal Fields
Data-driven surrogate models are widely used for applications such as de...
research
∙
09/18/2019
Diversified Arbitrary Style Transfer via Deep Feature Perturbation
Image style transfer is an underdetermined problem, where a large number...
research
∙
01/21/2019
On Compression of Unsupervised Neural Nets by Pruning Weak Connections
Unsupervised neural nets such as Restricted Boltzmann Machines(RBMs) and...
research
∙
12/18/2018
Consistent Robust Adversarial Prediction for General Multiclass Classification
We propose a robust adversarial prediction framework for general multicl...
research
∙
11/18/2018
