Supplementary Material.pdf

Li_Correlational_Image_Modeling_CVPR_2023_supplemental.pdf
Preview of Supplementary Material
🔗 Source: openaccess.thecvf.com
📊 Size: 721 KB
📄 Pages: 4 pages
⬇️ Downloads: 66

Summary

The supplementary material provides detailed pre-training and fine-tuning recipes for Correlational Image Modeling (CIM) using vanilla ViT and ResNet-50 models. Pre-training settings are shared across architectures, with 300 epochs, peak learning rate of 2.4e-3, and batch size of 4096. Fine-tuning settings vary between ViT and ResNet-50, with ViT fine-tuned for 200 epochs and ResNet-50 fine-tuned for 100 or 300 epochs. Additional qualitative visualizations of exemplar-context images and predicted correlation maps are provided.

Description

The supplementary material provides detailed pre-training and fine-tuning recipes for Correlational Image Modeling (CIM) using vanilla ViT and ResNet-50...

Technical Information

  • File Format: PDF
  • File Size: 721 KB
  • Pages: 4
  • Language: EN
  • Total Downloads: 66
  • Last Updated: 1 day ago

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