TwistNet-2D is a new CNN module that uses directional spiral shifts and normalized channel products to model local second-order texture interactions, outperforming larger backbones on four benchmarks with only 3.5% extra parameters.
Wightman, PyTorch image models,https://github.com/rwightman/pytorch-image-models
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TwistNet-2D: Learning Second-Order Channel Interactions via Spiral Twisting for Texture Recognition
TwistNet-2D is a new CNN module that uses directional spiral shifts and normalized channel products to model local second-order texture interactions, outperforming larger backbones on four benchmarks with only 3.5% extra parameters.