Patch-wise sparse MoE layers in CNNs for semantic segmentation yield architecture-dependent gains up to 3.9 mIoU on Cityscapes and BDD100K with low overhead, but show strong design sensitivity.
Condconv: Conditionally parameterized convolu- tions for efficient inference.Conference on Neural Informa- tion Processing Systems (NIPS/NeurIPS), 32, 2019
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Design and Behavior of Sparse Mixture-of-Experts Layers in CNN-based Semantic Segmentation
Patch-wise sparse MoE layers in CNNs for semantic segmentation yield architecture-dependent gains up to 3.9 mIoU on Cityscapes and BDD100K with low overhead, but show strong design sensitivity.