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Incorporating Network Built-in Priors in Weakly-Supervised Semantic Segmentation

Saleh, Fatemehsadat; Ali Akbarian, Mohammad Sadegh; Salzmann, Mathieu; Petersson, Lars; Alvarez, Jose; Gould, Stephen


Pixel-level annotations are expensive and time consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recently, CNN-based methods have proposed to fine-tune pre-trained networks using image tags. Without additional information, this leads to poor localization accuracy. This problem, however, was alleviated by making use of objectness priors to generate foreground/background masks. Unfortunately these priors either require...[Show more]

CollectionsANU Research Publications
Date published: 2017-06-08
Type: Journal article
Source: IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI: 10.1109/TPAMI.2017.2713785


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