Search Results for author: Chuang Zhu

Found 19 papers, 16 papers with code

Temporal Consistent Automatic Video Colorization via Semantic Correspondence

1 code implementation13 May 2023 Yu Zhang, Siqi Chen, Mingdao Wang, Xianlin Zhang, Chuang Zhu, Yue Zhang, Xueming Li

Extensive experiments demonstrate that our method outperforms other methods in maintaining temporal consistency both qualitatively and quantitatively.

Colorization Image Colorization +1

A Self-Training Framework Based on Multi-Scale Attention Fusion for Weakly Supervised Semantic Segmentation

1 code implementation10 May 2023 Guoqing Yang, Chuang Zhu, Yu Zhang

Weakly supervised semantic segmentation (WSSS) based on image-level labels is challenging since it is hard to obtain complete semantic regions.

Denoising Weakly supervised Semantic Segmentation +1

Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge Review

no code implementations5 May 2023 Chuang Zhu, ShengJie Liu, Feng Xu, Zekuan Yu, Arpit Aggarwal, Germán Corredor, Anant Madabhushi, Qixun Qu, Hongwei Fan, Fangda Li, Yueheng Li, Xianchao Guan, Yongbing Zhang, Vivek Kumar Singh, Farhan Akram, Md. Mostafa Kamal Sarker, Zhongyue Shi, Mulan Jin

For invasive breast cancer, immunohistochemical (IHC) techniques are often used to detect the expression level of human epidermal growth factor receptor-2 (HER2) in breast tissue to formulate a precise treatment plan.

Image Generation SSIM

Semi-supervised Domain Adaptation via Prototype-based Multi-level Learning

1 code implementation4 May 2023 Xinyang Huang, Chuang Zhu, Wenkai Chen

At the inter-domain level, we propose a cross-domain alignment loss to help the model use the target prototype for cross-domain knowledge transfer.

Domain Adaptation Pseudo Label +1

Hard-aware Instance Adaptive Self-training for Unsupervised Cross-domain Semantic Segmentation

1 code implementation14 Feb 2023 Chuang Zhu, Kebin Liu, Wenqi Tang, Ke Mei, Jiaqi Zou, Tiejun Huang

The divergence between labeled training data and unlabeled testing data is a significant challenge for recent deep learning models.

Model Optimization Pseudo Label +2

WUDA: Unsupervised Domain Adaptation Based on Weak Source Domain Labels

1 code implementation5 Oct 2022 ShengJie Liu, Chuang Zhu, Wenqi Tang

For scenarios where weak supervision and cross-domain problems coexist, this paper defines a new task: unsupervised domain adaptation based on weak source domain labels (WUDA).

Image Segmentation object-detection +4

Hard Sample Aware Noise Robust Learning for Histopathology Image Classification

1 code implementation5 Dec 2021 Chuang Zhu, Wenkai Chen, Ting Peng, Ying Wang, Mulan Jin

In this work, we introduce a novel hard sample aware noise robust learning method for histopathology image classification.

Classification Learning with noisy labels

Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides

1 code implementation4 Dec 2021 Feng Xu, Chuang Zhu, Wenqi Tang, Ying Wang, Yu Zhang, Jie Li, Hongchuan Jiang, Zhongyue Shi, Jun Liu, Mulan Jin

Conclusion: Our study provides a novel DL-based biomarker on primary tumor CNB slides to predict the metastatic status of ALN preoperatively for patients with EBC.

Multiple Instance Learning Specificity +1

Hard-sample Guided Hybrid Contrast Learning for Unsupervised Person Re-Identification

1 code implementation25 Sep 2021 Zheng Hu, Chuang Zhu, Gang He

However, the previous approaches did not fully exploit information of hard samples, simply using cluster centroid or all instances for contrastive learning.

Contrastive Learning Pseudo Label +1

LLVIP: A Visible-infrared Paired Dataset for Low-light Vision

1 code implementation24 Aug 2021 Xinyu Jia, Chuang Zhu, Minzhen Li, Wenqi Tang, ShengJie Liu, Wenli Zhou

It is very challenging for various visual tasks such as image fusion, pedestrian detection and image-to-image translation in low light conditions due to the loss of effective target areas.

Image Registration Image-to-Image Translation +6

Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark

1 code implementation24 Aug 2021 Shuhao Qiu, Chuang Zhu, Wenli Zhou

In recent years, deep learning-based methods have shown promising results in computer vision area.

Domain Adaptation Meta-Learning +2

Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet

2 code implementations29 Jun 2020 Chuang Zhu, Ke Mei, Ting Peng, Yihao Luo, Jun Liu, Ying Wang, Mulan Jin

The automatic and objective medical diagnostic model can be valuable to achieve early cancer detection, and thus reducing the mortality rate.

Tumor Segmentation

Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning

1 code implementation20 Feb 2020 Ke Mei, Chuang Zhu, Lei Jiang, Jun Liu, Yuanyuan Qiao

Experimental results on glomeruli segmentation from renal biopsy images indicate that our network is able to improve segmentation performance on target type of stained images and use unlabeled data to achieve similar accuracy to labeled data.

Highly Efficient Follicular Segmentation in Thyroid Cytopathological Whole Slide Image

1 code implementation13 Feb 2019 Siyan Tao, Yao Guo, Chuang Zhu, Huang Chen, Yue Zhang, Jie Yang, Jun Liu

In this paper, we propose a novel method for highly efficient follicular segmentation of thyroid cytopathological WSIs.

General Classification

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