Search Results for author: Zhihao Chen

Found 30 papers, 12 papers with code

Event-Triggered Observer-Based Fixed-Time Consensus Control for Uncertain Nonlinear Multiagent Systems with Unknown States

no code implementations31 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).

Spectral Enhancement and Pseudo-Anchor Guidance for Infrared-Visible Person Re-Identification

1 code implementation26 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.

Person Re-Identification

DAPONet: A Dual Attention and Partially Overparameterized Network for Real-Time Road Damage Detection

no code implementations3 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.

Road Damage Detection

HMT-UNet: A hybird Mamba-Transformer Vision UNet for Medical Image Segmentation

1 code implementation21 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).

Image Segmentation Mamba +4

Path-SAM2: Transfer SAM2 for digital pathology semantic segmentation

1 code implementation7 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.

Decoder Image Segmentation +5

Features Reconstruction Disentanglement Cloth-Changing Person Re-Identification

no code implementations15 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.

Cloth-Changing Person Re-Identification Disentanglement +1

HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation

1 code implementation3 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.

Image Segmentation Medical Image Segmentation +2

Reliable Source Approximation: Source-Free Unsupervised Domain Adaptation for Vestibular Schwannoma MRI Segmentation

1 code implementation25 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.

MRI segmentation Segmentation +1

Topicwise Separable Sentence Retrieval for Medical Report Generation

no code implementations7 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.

Decoder Medical Report Generation +3

MambaUIE&SR: Unraveling the Ocean's Secrets with Only 2.8 GFLOPs

1 code implementation22 Apr 2024 Zhihao Chen, Yiyuan Ge

In addition, combining CNN and Transformer can effectively combine global and local information for enhancement.

Mamba UIE

FLDM-VTON: Faithful Latent Diffusion Model for Virtual Try-on

no code implementations22 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.

Virtual Try-on

MedRG: Medical Report Grounding with Multi-modal Large Language Model

no code implementations10 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.

Decoder Language Modeling +5

Part-Attention Based Model Make Occluded Person Re-Identification Stronger

no code implementations4 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.

Human Parsing Occluded Person Re-Identification +1

OC4-ReID: Occluded Cloth-Changing Person Re-Identification

no code implementations13 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.

Cloth-Changing Person Re-Identification Triplet

Low-dose CT Denoising with Language-engaged Dual-space Alignment

1 code implementation10 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.

Computed Tomography (CT) Denoising

Exploiting Emotion-Semantic Correlations for Empathetic Response Generation

1 code implementation27 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.

Dialogue Generation Empathetic Response Generation +1

Training-free image style alignment for self-adapting domain shift on handheld ultrasound devices

no code implementations17 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.

IQAGPT: Image Quality Assessment with Vision-language and ChatGPT Models

no code implementations25 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.

Image Quality Assessment

ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT Denoising

1 code implementation23 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.

Anatomy Computed Tomography (CT) +2

Learning Physical-Spatio-Temporal Features for Video Shadow Removal

no code implementations16 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.

Shadow Removal Video Restoration

Medical Phrase Grounding with Region-Phrase Context Contrastive Alignment

no code implementations14 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).

Medical Image Analysis Phrase Grounding +1

LIT-Former: Linking In-plane and Through-plane Transformers for Simultaneous CT Image Denoising and Deblurring

1 code implementation21 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.

Computed Tomography (CT) Deblurring +2

Feature Transformation for Cross-domain Few-shot Remote Sensing Scene Classification

no code implementations4 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.

Cross-Domain Few-Shot Scene Classification

Triple-cooperative Video Shadow Detection

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.

Saliency Detection Semantic Segmentation +3

A Multi-Task Mean Teacher for Semi-Supervised 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)

Shadow Detection

Effects of Blur and Deblurring to Visual Object Tracking

no code implementations21 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.

Deblurring Image Deblurring +1

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