Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers-Reference-Cited by-同舟云学术

Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Ru Lixiang¹,Zhan Yibing²,Yu Baosheng³,Du Bo¹

Affiliation:

1. Institute of Artificial Intelligence, School of Computer Science and Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University,National Engineering Research Center for Multimedia Software,China

2. JD Explore Academy,China

3. The University of Sydney,Australia

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9878378/9878366/09878971.pdf?arnumber=9878971

Reference59 articles.

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2. Vision Transformers for Dense Prediction

3. From image-level to pixel-level labeling with Convolutional Networks

4. Weakly-and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation

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