Better segmentation by using the distribution of categories with MCIBI++
Better segmentation by using the distribution of categories with MCIBI++
MCIBI++: Soft Mining Contextual Information Beyond Image for Semantic Segmentation
arXiv paper abstract https://arxiv.org/abs/2209.04471v1
arXiv PDF paper https://arxiv.org/pdf/2209.04471v1.pdf
... semantic segmentation ... focus on modeling the contexts within image while neglecting the valuable semantics of the corresponding category beyond image.
... propose a novel soft mining contextual information beyond image paradigm named MCIBI++ to further boost the pixel-level representations.
... first ... store the dataset-level distribution information of various categories and then leverage the information to yield the dataset-level category representations during network forward.
... generate a class probability distribution for each pixel representation and conduct the dataset-level context aggregation with the class probability distribution as weights.
... MCIBI++ can be ... incorporated into the existing segmentation frameworks and ... can be extended into the video semantic segmentation
... achieved the state-of-the-art performance on seven challenging image or video semantic segmentation benchmarks.
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