Weakly-supervised Semantic Segmentation on Historical Document Images
Abstract
References
Index Terms
- Weakly-supervised Semantic Segmentation on Historical Document Images
Recommendations
Dual semantic-guided model for weakly-supervised zero-shot semantic segmentation
AbstractThe major obstacle in semantic segmentation is that it requires a large number of pixel-level labeled data to train an effective model. In order to reduce the cost of annotation, weakly-supervised methods use weaker labels to overcome the need for ...
Semi- and Weakly- Supervised Semantic Segmentation with Deep Convolutional Neural Networks
MM '15: Proceedings of the 23rd ACM international conference on MultimediaSuccessful semantic segmentation methods typically rely on the training datasets containing a large number of pixel-wise labeled images. To alleviate the dependence on such a fully annotated training dataset, in this paper, we propose a semi- and weakly-...
Dual-aware Domain Mining and Cross-aware Supervision for Weakly-supervised Semantic Segmentation
Weakly Supervised Semantic Segmentation with image-level annotation uses localization maps from the classifier to generate pseudo labels. However, such localization maps focus only on sparse salient object regions, it is difficult to generate high-quality ...
Comments
Information & Contributors
Information
Published In
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tag
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
Acceptance Rates
Upcoming Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 36Total Downloads
- Downloads (Last 12 months)28
- Downloads (Last 6 weeks)2
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in