no code implementations • 5 Apr 2024 • Mengting Li, Chuang Zhu
Therefore, it is crucial to combat noisy labels for computer vision tasks, especially for classification tasks.
1 code implementation • 27 Oct 2023 • Jeff Hwang, Moto Hira, Caroline Chen, Xiaohui Zhang, Zhaoheng Ni, Guangzhi Sun, Pingchuan Ma, Ruizhe Huang, Vineel Pratap, Yuekai Zhang, Anurag Kumar, Chin-Yun Yu, Chuang Zhu, Chunxi Liu, Jacob Kahn, Mirco Ravanelli, Peng Sun, Shinji Watanabe, Yangyang Shi, Yumeng Tao, Robin Scheibler, Samuele Cornell, Sean Kim, Stavros Petridis
TorchAudio is an open-source audio and speech processing library built for PyTorch.
no code implementations • 27 Sep 2023 • Nemin Qiu, Chuang Zhu
In this paper, our focus is on generating highly accurate and low-latency SNNs specifically for object detection.
no code implementations • 27 Sep 2023 • Nemin Qiu, Zhiguo Li, Yuan Li, Chuang Zhu
Then, we propose a scale-aware pseudoquantization scheme to guarantee the correctness of the compact ANN to SNN.
no code implementations • 5 Sep 2023 • Yongkang Zhao, Chuang Zhu, Yuan Li, Shuaishuai Wang, Zihan Lan, Yuanyuan Qiao
Detecting small moving targets accurately in infrared (IR) image sequences is a significant challenge.
1 code implementation • 25 Aug 2023 • Xinyang Huang, Chuang Zhu, Wenkai Chen
Cross-domain few-shot segmentation (CD-FSS) aims to achieve semantic segmentation in previously unseen domains with a limited number of annotated samples.
1 code implementation • 13 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.
1 code implementation • 10 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.
1 code implementation • 5 May 2023 • Chuang Zhu, ShengJie Liu, Zekuan Yu, Feng Xu, 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.
1 code implementation • 4 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.
1 code implementation • 14 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.
no code implementations • 7 Oct 2022 • Zhihao Wang, Chuang Zhu
In TCNL, the shallow feature extractor gets preliminary features first.
1 code implementation • 5 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).
1 code implementation • 25 Apr 2022 • ShengJie Liu, Chuang Zhu, Feng Xu, Xinyu Jia, Zhongyue Shi, Mulan Jin
The evaluation of human epidermal growth factor receptor 2 (HER2) expression is essential to formulate a precise treatment for breast cancer.
Ranked #1 on Image-to-Image Translation on BCI
Breast Cancer Detection Classification Of Breast Cancer Histology Images +4
1 code implementation • 5 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.
Ranked #1 on Learning with noisy labels on Chaoyang
1 code implementation • 4 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.
no code implementations • 4 Dec 2021 • Chuang Zhu, Zheng Hu, Huihui Dong, Gang He, Zekuan Yu, Shangshang Zhang
In this paper, we propose a robust sample generation scheme to construct informative triplets.
1 code implementation • 2 Dec 2021 • Wenkai Chen, Chuang Zhu, Yi Chen, Mengting Li, Tiejun Huang
Imperfect labels are ubiquitous in real-world datasets and seriously harm the model performance.
Ranked #1 on Learning with noisy labels on CIFAR-100N
1 code implementation • 25 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.
1 code implementation • 24 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.
Ranked #1 on Thermal Infrared Pedestrian Detection on LLVIP
1 code implementation • 24 Aug 2021 • Shuhao Qiu, Chuang Zhu, Wenli Zhou
In recent years, deep learning-based methods have shown promising results in computer vision area.
Ranked #1 on Scene Text Recognition on MSDA
2 code implementations • ECCV 2020 • Ke Mei, Chuang Zhu, Jiaqi Zou, Shanghang Zhang
In this paper, we propose an instance adaptive self-training framework for UDA on the task of semantic segmentation.
Ranked #13 on Image-to-Image Translation on SYNTHIA-to-Cityscapes
2 code implementations • 29 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.
Ranked #1 on Tumor Segmentation on DigestPath
1 code implementation • 20 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.
1 code implementation • 13 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.