AutoML
Shape Adaptor
Introduced by Liu et al. in Shape Adaptor: A Learnable Resizing ModuleShape Adaptor is a novel resizing module for neural networks. It is a drop-in enhancement built on top of traditional resizing layers, such as pooling, bilinear sampling, and strided convolution. This module allows for a learnable shaping factor which differs from the traditional resizing layers that are fixed and deterministic.
Image Source: Liu et al.
Source: Shape Adaptor: A Learnable Resizing Module
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 |
