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Google AI Blog: Axial-DeepLab: Long-Range Modeling …

Details: Note that a message or feature vector at (x1, y1) can always be passed globally on a 2D lattice to any position (x2, y2), with one hop on the height-axis (x1, y1 →x1, y2), followed by another hop on the width axis (x1, y2 → x2, y2).In this way, we are able to model 2D long-range relations in a single residual block. This axial-attention design also reduces the complexity from quadratic to

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