Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features-Reference-Cited by-同舟云学术

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Weakly-Supervised Semantic Segmentation by Iteratively Mining Common Object Features

Published:2018-06 Issue: Volume: Page:
ISSN:
Container-title:2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
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Author:

Wang Xiang,You Shaodi,Li Xi,Ma Huimin

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8576498/8578098/08578245.pdf?arnumber=8578245

Cited by 243 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Decoupling foreground and background with Siamese ViT networks for weakly-supervised semantic segmentation;Neurocomputing;2024-12

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3. D2Net: discriminative feature extraction and details preservation network for salient object detection;Journal of Electronic Imaging;2024-08-16

4. Pairwise-Pixel Self-Supervised and Superpixel-Guided Prototype Contrastive Loss for Weakly Supervised Semantic Segmentation;Cognitive Computation;2024-05

5. Weakly-semi supervised extraction of rooftop photovoltaics from high-resolution images based on segment anything model and class activation map;Applied Energy;2024-05

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