Skip to content

Latest commit

 

History

History
11 lines (8 loc) · 717 Bytes

GETTING_STARTED_FULL.md

File metadata and controls

11 lines (8 loc) · 717 Bytes

Getting started with fully-supervised learning of CAST

Our CAST can also be trained with fully-supervised learning. In the paper, we fine-tune pre-trained models on ADE20K and Pascal Context for semantic segmentation. We pre-train models for fully-supervised classification with DeiT framework.

We provide the bashscripts for running fully-supervised experiments. By default, we use CAST-S. You can use larger models, e.g. CAST-B by replacing --model cast_small with --model cast_base in the bashscripts.

Pre-train on ImageNet for classification

  1. fully-supervised learning of CAST on ImageNet-1K:
> bash scripts/deit/train_imagenet1k_cast.sh