Convolutions
ShapeConv
Introduced by Cao et al. in ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic SegmentationShapeConv, or Shape-aware Convolutional layer, is a convolutional layer for processing the depth feature in indoor RGB-D semantic segmentation. The depth feature is firstly decomposed into a shape-component and a base-component, next two learnable weights are introduced to cooperate with them independently, and finally a convolution is applied on the re-weighted combination of these two components.
Source: ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentation
Papers
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Usage Over Time
Components
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| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
