43 citations · 74 across the 12 of their papers we have counts for
12 papers
StyleDiffusion: Controllable Disentangled Style Transfer via Diffusion Models
Zhizhong Wang, Lei Zhao, Wei Xing
Content and style (C-S) disentanglement is a fundamental problem and critical challenge of style transfer. Existing approaches based on explicit definitions (e.g., Gram matrix) or…
VGOS: Voxel Grid Optimization for View Synthesis from Sparse Inputs
Jiakai Sun, Zhanjie Zhang, Jiafu Chen +5
Neural Radiance Fields (NeRF) has shown great success in novel view synthesis due to its state-of-the-art quality and flexibility. However, NeRF requires dense input views (tens to…
Joint Optimization of Triangle Mesh, Material, and Light from Neural Fields with Neural Radiance Cache
Jiakai Sun, Weijing Zhang, Zhanjie Zhang +4
Traditional inverse rendering techniques are based on textured meshes, which naturally adapts to modern graphics pipelines, but costly differentiable multi-bounce Monte Carlo (MC)…
Generative Image Inpainting with Segmentation Confusion Adversarial Training and Contrastive Learning
Zhiwen Zuo, Lei Zhao, Ailin Li +5
This paper presents a new adversarial training framework for image inpainting with segmentation confusion adversarial training (SCAT) and contrastive learning. SCAT plays an advers…
MicroAST: Towards Super-Fast Ultra-Resolution Arbitrary Style Transfer
Zhizhong Wang, Lei Zhao, Zhiwen Zuo +4
Arbitrary style transfer (AST) transfers arbitrary artistic styles onto content images. Despite the recent rapid progress, existing AST methods are either incapable or too slow to…
AesUST: Towards Aesthetic-Enhanced Universal Style Transfer
Zhizhong Wang, Zhanjie Zhang, Lei Zhao +4
Recent studies have shown remarkable success in universal style transfer which transfers arbitrary visual styles to content images. However, existing approaches suffer from the aes…
Texture Reformer: Towards Fast and Universal Interactive Texture Transfer
Zhizhong Wang, Lei Zhao, Haibo Chen +4
In this paper, we present the texture reformer, a fast and universal neural-based framework for interactive texture transfer with user-specified guidance. The challenges lie in thr…
DivSwapper: Towards Diversified Patch-based Arbitrary Style Transfer
Zhizhong Wang, Lei Zhao, Haibo Chen +4
Gram-based and patch-based approaches are two important research lines of style transfer. Recent diversified Gram-based methods have been able to produce multiple and diverse styli…
Multimodal Image-to-Image Translation via Mutual Information Estimation and Maximization
Zhiwen Zuo, Lei Zhao, Zhizhong Wang +5
Multimodal image-to-image translation (I2IT) aims to learn a conditional distribution that explores multiple possible images in the target domain given an input image in the source…
Diversified Arbitrary Style Transfer via Deep Feature Perturbation
Zhizhong Wang, Lei Zhao, Haibo Chen +5
Image style transfer is an underdetermined problem, where a large number of solutions can satisfy the same constraint (the content and style). Although there have been some efforts…
On Compression of Unsupervised Neural Nets by Pruning Weak Connections
Zhiwen Zuo, Lei Zhao, Liwen Zuo +3
Unsupervised neural nets such as Restricted Boltzmann Machines(RBMs) and Deep Belif Networks(DBNs), are powerful in automatic feature extraction,unsupervised weight initialization…
GLStyleNet: Higher Quality Style Transfer Combining Global and Local Pyramid Features
Zhizhong Wang, Lei Zhao, Wei Xing +1
Recent studies using deep neural networks have shown remarkable success in style transfer especially for artistic and photo-realistic images. However, the approaches using global f…