Sep 5, 2019 · In this work, we propose to generate a scale- and shape-variant semantic mask for each pixel to confine its contextual region.
Semantic Segmentation needs to simultaneously deal with object recognition and localization, and hence should build the dense feature connections among large ...
It helps control the information flow within network via deciding what information to be passed or suppressed.
[CVPR-2019] Semantic Correlation Promoted Shape-Variant Context for Segmentation. 32 stars 0 forks Branches Tags Activity.
This work proposes a novel paired convolution to infer the semantic correlation of the pair and based on that to generate a shape mask, ...
In this work, we propose to generate a scale- and shape-variant semantic mask for each pixel to confine its contextual region. To this end, we first propose a ...
Context is essential for semantic segmentation. Due to the diverse shapes of objects and their complex layout in various scene images, the spatial scales and ...
His research interests broadly include machine learning and computer vision. Specifically, he focuses on scene understanding (e.g., image/video segmentation, ...
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation ... Semantic Correlation Promoted Shape-Variant Context for Segmentation.
81.0%. Semantic Correlation Promoted Shape-Variant Context for Segmentation. 2019. ResNet. 47. D3Net-L. 80.8%. Densely connected multidilated convolutional ...