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Sungmin Lee

2 accepted papers

2019

FickleNet: Weakly and Semi-Supervised Semantic Image Segmentation Using Stochastic Inference

CVPR 2019poster

The main obstacle to weakly supervised semantic image segmentation is the difficulty of obtaining pixel-level information from coarse image-level annotations. Most methods based on image-level annotations use localization maps obtained from the classifier, but these only focus on the small discrimin…

Cited by 557PDFScholar
2019

Frame-to-Frame Aggregation of Active Regions in Web Videos for Weakly Supervised Semantic Segmentation

ICCV 2019poster

When a deep neural network is trained on data with only image-level labeling, the regions activated in each image tend to identify only a small region of the target object. We propose a method of using videos automatically harvested from the web to identify a larger region of the target object by us…

Cited by 45PDFScholar