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Found 3 papers, 2 papers with code
Initializing Models with Larger Ones
Weight selection offers a new approach to leverage the power of pretrained models in resource-constrained settings, and we hope it can be a useful tool for training small models in the large-model era.
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy
Modern computer vision offers a great variety of models to practitioners, and selecting a model from multiple options for specific applications can be challenging.
MixMask: Revisiting Masking Strategy for Siamese ConvNets
These include (I) the inability to drop uninformative masked regions in ConvNets as they process data continuously, resulting in low training efficiency compared to ViT models; and (II) the mismatch between erase-based masking and the contrastive-based objective in Siamese ConvNets, which differs from the MIM approach.
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