no code implementations • 31 Dec 2024 • Kewei Zhou, ZiMing Wang, Zhihao Chen, Xin Wang
This paper introduces a novel approach for achieving fixed-time tracking consensus control in multiagent systems (MASs).
1 code implementation • 26 Dec 2024 • Yiyuan Ge, Zhihao Chen, Ziyang Wang, Jiaju Kang, Mingya Zhang
The development of deep learning has facilitated the application of person re-identification (ReID) technology in intelligent security.
no code implementations • 3 Sep 2024 • Weichao Pan, Jiaju Kang, Xu Wang, Zhihao Chen, Yiyuan Ge
Current road damage detection methods, relying on manual inspections or sensor-mounted vehicles, are inefficient, limited in coverage, and often inaccurate, especially for minor damages, leading to delays and safety hazards.
1 code implementation • 21 Aug 2024 • Mingya Zhang, Zhihao Chen, Yiyuan Ge, Xianping Tao
In this paper, leveraging the hybrid mechanism of SSM, we propose a U-shape architecture model for medical image segmentation, named Hybird Transformer vision Mamba UNet (HTM-UNet).
1 code implementation • 7 Aug 2024 • Mingya Zhang, Liang Wang, Zhihao Chen, Yiyuan Ge, Xianping Tao
The semantic segmentation task in pathology plays an indispensable role in assisting physicians in determining the condition of tissue lesions.
no code implementations • 15 Jul 2024 • Zhihao Chen, Yiyuan Ge, Qing Yue
However, due to the lack of ground truth, these methods inevitably introduce noise, which destroys the discriminative features and leads to an uncontrollable disentanglement process.
1 code implementation • 3 Jul 2024 • Tao Chen, Chenhui Wang, Zhihao Chen, Yiming Lei, Hongming Shan
In this work, we propose to complement discriminative segmentation methods with the knowledge of underlying data distribution from generative models.
1 code implementation • 25 May 2024 • Hongye Zeng, Ke Zou, Zhihao Chen, Rui Zheng, Huazhu Fu
Source-Free Unsupervised Domain Adaptation (SFUDA) has recently become a focus in the medical image domain adaptation, as it only utilizes the source model and does not require annotated target data.
no code implementations • 7 May 2024 • Junting Zhao, Yang Zhou, Zhihao Chen, Huazhu Fu, Liang Wan
To ensure comprehensive learning of both common and rare topics, we categorize queries into common and rare types to learn differentiated topics, and then propose Topic Contrastive Loss to effectively align topics and queries in the latent space.
1 code implementation • 22 Apr 2024 • Zhihao Chen, Yiyuan Ge
In addition, combining CNN and Transformer can effectively combine global and local information for enhancement.
no code implementations • 22 Apr 2024 • Chenhui Wang, Tao Chen, Zhihao Chen, Zhizhong Huang, Taoran Jiang, Qi Wang, Hongming Shan
Despite their impressive generative performance, latent diffusion model-based virtual try-on (VTON) methods lack faithfulness to crucial details of the clothes, such as style, pattern, and text.
no code implementations • 10 Apr 2024 • Ke Zou, Yang Bai, Zhihao Chen, Yang Zhou, Yidi Chen, Kai Ren, Meng Wang, Xuedong Yuan, Xiaojing Shen, Huazhu Fu
Medical Report Grounding is pivotal in identifying the most relevant regions in medical images based on a given phrase query, a critical aspect in medical image analysis and radiological diagnosis.
no code implementations • 4 Apr 2024 • Zhihao Chen, Yiyuan Ge
However, occluded person ReID still suffers from background clutter and low-quality local feature representations, which limits model performance.
no code implementations • 13 Mar 2024 • Zhihao Chen, Yiyuan Ge, Ziyang Wang, Jiaju Kang, Mingya Zhang
The study of Cloth-Changing Person Re-identification (CC-ReID) focuses on retrieving specific pedestrians when their clothing has changed, typically under the assumption that the entire pedestrian images are visible.
1 code implementation • 10 Mar 2024 • Zhihao Chen, Tao Chen, Chenhui Wang, Chuang Niu, Ge Wang, Hongming Shan
While various deep learning methods were proposed for low-dose computed tomography (CT) denoising, they often suffer from over-smoothing, blurring, and lack of explainability.
1 code implementation • 27 Feb 2024 • Zhou Yang, Zhaochun Ren, Yufeng Wang, Xiaofei Zhu, Zhihao Chen, Tiecheng Cai, Yunbing Wu, Yisong Su, Sibo Ju, Xiangwen Liao
Based on dynamic emotion-semantic vectors and dependency trees, we propose a dynamic correlation graph convolutional network to guide the model in learning context meanings in dialogue and generating empathetic responses.
no code implementations • 17 Feb 2024 • Hongye Zeng, Ke Zou, Zhihao Chen, Yuchong Gao, Hongbo Chen, Haibin Zhang, Kang Zhou, Meng Wang, Rick Siow Mong Goh, Yong liu, Chang Jiang, Rui Zheng, Huazhu Fu
Moreover, the models trained on standard ultrasound device data are constrained by training data distribution and perform poorly when directly applied to handheld device data.
no code implementations • 25 Dec 2023 • Zhihao Chen, Bin Hu, Chuang Niu, Tao Chen, Yuxin Li, Hongming Shan, Ge Wang
Second, we fine-tune the image quality captioning VLM on the CT-IQA dataset to generate quality descriptions.
no code implementations • 16 Aug 2023 • Zhiyu Ma, Chen Li, Tianming Du, Le Zhang, Dechao Tang, Deguo Ma, Shanchuan Huang, Yan Liu, Yihao Sun, Zhihao Chen, Jin Yuan, Qianqing Nie, Marcin Grzegorzek, Hongzan Sun
In the comparative study of semantic segmentation of abdominal adipose tissue, the segmentation results of adipose tissue by each model show different structural characteristics.
1 code implementation • 23 Jul 2023 • Zhihao Chen, Qi Gao, Yi Zhang, Hongming Shan
In this paper, we propose a novel Anatomy-aware Supervised CONtrastive learning framework, termed ASCON, which can explore the anatomical semantics for low-dose CT denoising while providing anatomical interpretability.
no code implementations • 16 Mar 2023 • Zhihao Chen, Liang Wan, Yefan Xiao, Lei Zhu, Huazhu Fu
Then, we develop a progressive aggregation module to enhance the spatio and temporal characteristics of features maps, and effectively integrate the three kinds of features.
no code implementations • 14 Mar 2023 • Zhihao Chen, Yang Zhou, Anh Tran, Junting Zhao, Liang Wan, Gideon Ooi, Lionel Cheng, Choon Hua Thng, Xinxing Xu, Yong liu, Huazhu Fu
To enable MedRPG to locate nuanced medical findings with better region-phrase correspondences, we further propose Tri-attention Context contrastive alignment (TaCo).
1 code implementation • 21 Feb 2023 • Zhihao Chen, Chuang Niu, Qi Gao, Ge Wang, Hongming Shan
Here, we propose to link in-plane and through-plane transformers for simultaneous in-plane denoising and through-plane deblurring, termed as LIT-Former, which can efficiently synergize in-plane and through-plane sub-tasks for 3D CT imaging and enjoy the advantages of both convolution and transformer networks.
no code implementations • 16 Feb 2023 • Ke Zou, Zhihao Chen, Xuedong Yuan, Xiaojing Shen, Meng Wang, Huazhu Fu
We further discuss how they can be estimated in medical imaging.
no code implementations • 4 Mar 2022 • Qiaoling Chen, Zhihao Chen, Wei Luo
Moreover, FTM can be effectively learned on target domain in the case of few training data available and is agnostic to specific network structures.
no code implementations • 9 Aug 2021 • Alain Lalande, Zhihao Chen, Thibaut Pommier, Thomas Decourselle, Abdul Qayyum, Michel Salomon, Dominique Ginhac, Youssef Skandarani, Arnaud Boucher, Khawla Brahim, Marleen de Bruijne, Robin Camarasa, Teresa M. Correia, Xue Feng, Kibrom B. Girum, Anja Hennemuth, Markus Huellebrand, Raabid Hussain, Matthias Ivantsits, Jun Ma, Craig Meyer, Rishabh Sharma, Jixi Shi, Nikolaos V. Tsekos, Marta Varela, Xiyue Wang, Sen yang, Hannu Zhang, Yichi Zhang, Yuncheng Zhou, Xiahai Zhuang, Raphael Couturier, Fabrice Meriaudeau
The publicly available database consists of 150 exams divided into 50 cases with normal MRI after injection of a contrast agent and 100 cases with myocardial infarction (and then with a hyperenhanced area on DE-MRI), whatever their inclusion in the cardiac emergency department.
no code implementations • 8 Jul 2021 • Zhihao Chen, Jie Gao, Weikai Wang, Zheng Yan
The generative neural network takes the mask as prior for the second-stage refined predictions.
1 code implementation • CVPR 2021 • Zhihao Chen, Liang Wan, Lei Zhu, Jia Shen, Huazhu Fu, Wennan Liu, Jing Qin
The bottleneck is the lack of a well-established dataset with high-quality annotations for video shadow detection.
1 code implementation • CVPR 2020 • Zhihao Chen, Lei Zhu, Liang Wan, Song Wang, Wei Feng, Pheng-Ann Heng
To boost the shadow detection performance, this paper presents a multi-task mean teacher model for semi-supervised shadow detection by leveraging unlabeled data and exploring the learning of multiple information of shadows simultaneously.
Ranked #5 on
Shadow Detection
on CUHK-Shadow
(using extra training data)
no code implementations • 21 Aug 2019 • Qing Guo, Wei Feng, Zhihao Chen, Ruijun Gao, Liang Wan, Song Wang
In this paper, we address these two problems by constructing a Blurred Video Tracking benchmark, which contains a variety of videos with different levels of motion blurs, as well as ground truth tracking results for evaluating trackers.