mlsanityData to 14 Oct 2026

Don't worry about mistakes! Glass Segmentation Network via Mistake Correction

arXiv 2304.10825 ↗First posted 21 Apr 2023cs.CVcited by 1

Not on the map. Why?

Abstract (arXiv)

Recall one time when we were in an unfamiliar mall. We might mistakenly think that there exists or does not exist a piece of glass in front of us. Such mistakes will remind us to walk more safely and freely at the same or a similar place next time. To absorb the human mistake correction wisdom, we propose a novel glass segmentation network to detect transparent glass, dubbed GlassSegNet. Motivated by this human behavior, GlassSegNet utilizes two key stages: the identification stage (IS) and the correction stage (CS). The IS is designed to simulate the detection procedure of human recognition for identifying transparent glass by global context and edge information. The CS then progressively refines the coarse prediction by correcting mistake regions based on gained experience. Extensive experiments show clear improvements of our GlassSegNet over thirty-four state-of-the-art methods on three benchmark datasets.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 41 of its 74 references that are in the map. First posted on arXiv 21 Apr 2023.

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41 of 74 references.

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