Slimmable ConvNeXt adapts ConvNeXt for width-adaptive inference using LayerNorm and inverted bottlenecks, reaching 80.8% top-1 at 4.5 GMACs and outperforming HydraViT, MatFormer, and SortedNet on ImageNet-1k.
Machine learning with com- puter networks: Techniques, datasets, and models.IEEE Ac- cess, 12:54673–54720, 2024
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Slimmable ConvNeXt: Width-Adaptive Inference for Efficient Multi-Device Deployment
Slimmable ConvNeXt adapts ConvNeXt for width-adaptive inference using LayerNorm and inverted bottlenecks, reaching 80.8% top-1 at 4.5 GMACs and outperforming HydraViT, MatFormer, and SortedNet on ImageNet-1k.