arXiv:2007.14902
공식 코드 · Papers with Code
Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation
원문 초록
In this paper, to remedy this deficiency, we propose a Linear Attention Mechanism which is approximate to dot-product attention with much less memory and computational costs. The efficient design makes the incorporation between attention mechanisms and neural networks more flexible and versatile. Experiments conducted on semantic segmentation demonstrated the effectiveness of linear attention mechanism. Code is available at https://github.com/lironui/Linear-Attention-Mechanism.
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A New Dataset and Performance Benchmark for Real-time Spacecraft Segmentation in Onboard Flight Computers
Rethinking Query-based Transformer for Continual Image Segmentation
HNOSeg-XS: Extremely Small Hartley Neural Operator for Efficient and Resolution-Robust 3D Image Segmentation
토론
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