Search Results for author: Chunna Tian

Found 9 papers, 0 papers with code

Multi Task Consistency Guided Source-Free Test-Time Domain Adaptation Medical Image Segmentation

no code implementations18 Oct 2023 Yanyu Ye, Zhenxi Zhang, Wei Wei, Chunna Tian

To improve the performance of test-time domain adaptation, we propose a multi task consistency guided source-free test-time domain adaptation medical image segmentation method which ensures the consistency of the local boundary predictions and the global prototype representation.

Domain Adaptation Image Segmentation +4

Cross-supervised Dual Classifiers for Semi-supervised Medical Image Segmentation

no code implementations25 May 2023 Zhenxi Zhang, Ran Ran, Chunna Tian, Heng Zhou, Fan Yang, Xin Li, Zhicheng Jiao

This paper proposes a cross-supervised learning framework based on dual classifiers (DC-Net), including an evidential classifier and a vanilla classifier.

Image Segmentation Segmentation +2

Self-aware and Cross-sample Prototypical Learning for Semi-supervised Medical Image Segmentation

no code implementations25 May 2023 Zhenxi Zhang, Ran Ran, Chunna Tian, Heng Zhou, Xin Li, Fan Yang, Zhicheng Jiao

To address these issues, we propose a self-aware and cross-sample prototypical learning method (SCP-Net) to enhance the diversity of prediction in consistency learning by utilizing a broader range of semantic information derived from multiple inputs.

Image Segmentation Semantic Segmentation +1

Position-Aware Relation Learning for RGB-Thermal Salient Object Detection

no code implementations21 Sep 2022 Heng Zhou, Chunna Tian, Zhenxi Zhang, Chengyang Li, Yuxuan Ding, Yongqiang Xie, Zhongbo Li

FRDF utilizes the directional information between object pixels to effectively enhance the intra-class compactness of salient regions.

object-detection Object Detection +1

Don't Stop Learning: Towards Continual Learning for the CLIP Model

no code implementations19 Jul 2022 Yuxuan Ding, Lingqiao Liu, Chunna Tian, Jingyuan Yang, Haoxuan Ding

The Contrastive Language-Image Pre-training (CLIP) Model is a recently proposed large-scale pre-train model which attracts increasing attention in the computer vision community.

Continual Learning Image-text matching +2

Mutual- and Self- Prototype Alignment for Semi-supervised Medical Image Segmentation

no code implementations3 Jun 2022 Zhenxi Zhang, Chunna Tian, Zhicheng Jiao

In specific, mutual-prototype alignment enhances the information interaction between labeled and unlabeled data.

Image Segmentation Segmentation +2

PixelGame: Infrared small target segmentation as a Nash equilibrium

no code implementations26 May 2022 Heng Zhou, Chunna Tian, Zhenxi Zhang, Chengyang Li, Yongqiang Xie, Zhongbo Li

FNs-player and FPs-player are designed with different strategies: One is to minimize FNs and the other is to minimize FPs.

Collaborative Boundary-aware Context Encoding Networks for Error Map Prediction

no code implementations25 Jun 2020 Zhenxi Zhang, Chunna Tian, Jie Li, Zhusi Zhong, Zhicheng Jiao, Xinbo Gao

Further, we propose a context encoding module to utilize the global predictor from the error map to enhance the feature representation and regularize the networks.

Image Segmentation Medical Image Segmentation +2

Reweighted Laplace Prior Based Hyperspectral Compressive Sensing for Unknown Sparsity

no code implementations CVPR 2015 Lei Zhang, Wei Wei, Yanning Zhang, Chunna Tian, Fei Li

To address this problem, a novel reweighted Laplace prior based hyperspectral compressive sensing method is proposed in this study.

Compressive Sensing Noise Estimation

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