Search Results for author: Han Yang

Found 22 papers, 13 papers with code

NLUT: Neural-based 3D Lookup Tables for Video Photorealistic Style Transfer

1 code implementation16 Mar 2023 Yaosen Chen, Han Yang, Yuexin Yang, Yuegen Liu, Wei Wang, Xuming Wen, Chaoping Xie

However, existing methods obtain stylized video sequences by performing frame-by-frame photorealistic style transfer, which is inefficient and does not ensure the temporal consistency of the stylized video.

Style Transfer

Lung Nodule Segmentation and Low-Confidence Region Prediction with Uncertainty-Aware Attention Mechanism

no code implementations15 Mar 2023 Han Yang, Qiuli Wang, Yue Zhang, Zhulin An, Chen Liu

In UAAM, we propose a Multi-Confidence Mask (MCM), which is a combination of a Low-Confidence (LC) Mask and a High-Confidence (HC) Mask.

Lung Nodule Segmentation

Retinex-qDPC: automatic background rectified quantitative differential phase contrast imaging

no code implementations21 Jul 2022 Shuhe Zhang, Tao Peng, Zeyu Ke, Han Yang, Tos T. J. M. Berendschot, Jinhua Zhou

To tackle the mismatch of background and increases the experimental robustness, we propose the Retinex-qDPC in which we use the images edge features as data fidelity term yielding L2-Retinex-qDPC and L1-Retinex-qDPC for high background-robustness qDPC reconstruction.

Understanding and Improving Graph Injection Attack by Promoting Unnoticeability

1 code implementation ICLR 2022 Yongqiang Chen, Han Yang, Yonggang Zhang, Kaili Ma, Tongliang Liu, Bo Han, James Cheng

Recently Graph Injection Attack (GIA) emerges as a practical attack scenario on Graph Neural Networks (GNNs), where the adversary can merely inject few malicious nodes instead of modifying existing nodes or edges, i. e., Graph Modification Attack (GMA).

Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

2 code implementations11 Feb 2022 Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng

Despite recent success in using the invariance principle for out-of-distribution (OOD) generalization on Euclidean data (e. g., images), studies on graph data are still limited.

Drug Discovery Graph Learning +1

Uncertainty-Guided Lung Nodule Segmentation with Feature-Aware Attention

no code implementations24 Oct 2021 Han Yang, Lu Shen, Mengke Zhang, Qiuli Wang

With an Uncertainty-Aware Module, this network can provide a Multi-Confidence Mask (MCM), pointing out regions with different segmentation uncertainty levels.

Lung Nodule Segmentation

Disentangled Cycle Consistency for Highly-realistic Virtual Try-On

1 code implementation CVPR 2021 Chongjian Ge, Yibing Song, Yuying Ge, Han Yang, Wei Liu, Ping Luo

To this end, DCTON can be naturally trained in a self-supervised manner following cycle consistency learning.

Virtual Try-on

Improving Graph Representation Learning by Contrastive Regularization

no code implementations27 Jan 2021 Kaili Ma, Haochen Yang, Han Yang, Tatiana Jin, Pengfei Chen, Yongqiang Chen, Barakeel Fanseu Kamhoua, James Cheng

Graph representation learning is an important task with applications in various areas such as online social networks, e-commerce networks, WWW, and semantic webs.

Contrastive Learning Graph Representation Learning

Time-Continuous Energy-Conservation Neural Network for Structural Dynamics Analysis

no code implementations16 Dec 2020 Yuan Feng, Hexiang Wang, Han Yang, Fangbo Wang

Although the basic neural network provides an alternative approach for structural dynamics analysis, the lack of physics law inside the neural network limits the model accuracy and fidelity.

Rethinking Graph Regularization for Graph Neural Networks

1 code implementation4 Sep 2020 Han Yang, Kaili Ma, James Cheng

The graph Laplacian regularization term is usually used in semi-supervised representation learning to provide graph structure information for a model $f(X)$.

Node Classification Representation Learning

Towards Photo-Realistic Virtual Try-On by Adaptively Generating-Preserving Image Content

1 code implementation CVPR 2020 Han Yang, Ruimao Zhang, Xiaobao Guo, Wei Liu, Wangmeng Zuo, Ping Luo

Second, a clothes warping module warps clothes image according to the generated semantic layout, where a second-order difference constraint is introduced to stabilize the warping process during training. Third, an inpainting module for content fusion integrates all information (e. g. reference image, semantic layout, warped clothes) to adaptively produce each semantic part of human body.

Semantic Segmentation Virtual Try-on

CPR-GCN: Conditional Partial-Residual Graph Convolutional Network in Automated Anatomical Labeling of Coronary Arteries

no code implementations CVPR 2020 Han Yang, Xingjian Zhen, Ying Chi, Lei Zhang, Xian-Sheng Hua

On the technical side, the Partial-Residual GCN takes the position features of the branches, with the 3D spatial image features as conditions, to predict the label for each branches.


Towards Photo-Realistic Virtual Try-On by Adaptively Generating$\leftrightarrow$Preserving Image Content

3 code implementations12 Mar 2020 Han Yang, Ruimao Zhang, Xiaobao Guo, Wei Liu, WangMeng Zuo, Ping Luo

First, a semantic layout generation module utilizes semantic segmentation of the reference image to progressively predict the desired semantic layout after try-on.

Ranked #4 on Virtual Try-on on VITON (IS metric)

Semantic Segmentation Virtual Try-on

Self-Enhanced GNN: Improving Graph Neural Networks Using Model Outputs

1 code implementation18 Feb 2020 Han Yang, Xiao Yan, Xinyan Dai, Yongqiang Chen, James Cheng

In this paper, we propose self-enhanced GNN (SEG), which improves the quality of the input data using the outputs of existing GNN models for better performance on semi-supervised node classification.

General Classification Node Classification

Convolutional Embedding for Edit Distance

2 code implementations31 Jan 2020 Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, James Cheng

Edit-distance-based string similarity search has many applications such as spell correction, data de-duplication, and sequence alignment.

Hyper-Sphere Quantization: Communication-Efficient SGD for Federated Learning

1 code implementation12 Nov 2019 Xinyan Dai, Xiao Yan, Kaiwen Zhou, Han Yang, Kelvin K. W. Ng, James Cheng, Yu Fan

In particular, at the high compression ratio end, HSQ provides a low per-iteration communication cost of $O(\log d)$, which is favorable for federated learning.

Federated Learning Quantization

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