Search Results for author: Jun Wei

Found 8 papers, 5 papers with code

BoxPolyp:Boost Generalized Polyp Segmentation Using Extra Coarse Bounding Box Annotations

no code implementations7 Dec 2022 Jun Wei, Yiwen Hu, Guanbin Li, Shuguang Cui, S Kevin Zhou, Zhen Li

In practice, box annotations are applied to alleviate the over-fitting issue of previous polyp segmentation models, which generate fine-grained polyp area through the iterative boosted segmentation model.

What is the cost of adding a constraint in linear least squares?

no code implementations24 Jan 2022 Ramakrishna Kakarala, Jun Wei

Although the theory of constrained least squares (CLS) estimation is well known, it is usually applied with the view that the constraints to be imposed are unavoidable.

Shallow Feature Matters for Weakly Supervised Object Localization

1 code implementation CVPR 2021 Jun Wei, Qin Wang, Zhen Li, Sheng Wang, S. Kevin Zhou, Shuguang Cui

In practice, our SPOL model first generates the CAMs through a novel element-wise multiplication of shallow and deep feature maps, which filters the background noise and generates sharper boundaries robustly.

Pseudo Label Weakly-Supervised Object Localization

Label Decoupling Framework for Salient Object Detection

1 code implementation CVPR 2020 Jun Wei, Shuhui Wang, Zhe Wu, Chi Su, Qingming Huang, Qi Tian

Though remarkable progress has been achieved, we observe that the closer the pixel is to the edge, the more difficult it is to be predicted, because edge pixels have a very imbalance distribution.

object-detection RGB Salient Object Detection +2

MedSRGAN: medical images super-resolution using generative adversarial networks

1 code implementation Springer 2020 Yuchong Gu, Zitao Zen, Haibin Chen, Jun Wei, Yaqin Zhang, Binghui Chen, Yingqin Li, Yujuan Qin, Qing Xie, Zhuoren Jiang, Yao Lu

Super-resolution (SR) in medical imaging is an emerging application in medical imaging due to the needs of high quality images acquired with limited radiation dose, such as low dose Computer Tomography (CT), low field magnetic resonance imaging (MRI).


F3Net: Fusion, Feedback and Focus for Salient Object Detection

4 code implementations26 Nov 2019 Jun Wei, Shuhui Wang, Qingming Huang

Furthermore, different from binary cross entropy, the proposed PPA loss doesn't treat pixels equally, which can synthesize the local structure information of a pixel to guide the network to focus more on local details.

Dichotomous Image Segmentation object-detection +1

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