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Download following datasets:

1. PASCAL-5i

Download PASCAL VOC2012 devkit (train/val data):

wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar

Download PASCAL VOC2012 SDS extended mask annotations.

2. COCO-20i

Download COCO2014 train/val images and annotations:

wget http://images.cocodataset.org/zips/train2014.zip
wget http://images.cocodataset.org/zips/val2014.zip
wget http://images.cocodataset.org/annotations/annotations_trainval2014.zip

Download COCO2014 train/val annotations. (and locate both train2014/ and val2014/ under annotations/ directory).

Create a directory '../dataset' for the above few-shot segmentation datasets and appropriately place each dataset to have following directory structure:

Datasets/
  β”œβ”€β”€ VOC2012/            # PASCAL VOC2012 devkit
  β”‚   β”œβ”€β”€ Annotations/
  β”‚   β”œβ”€β”€ ImageSets/
  β”‚   β”œβ”€β”€ ...
  β”‚   └── SegmentationClassAug/
  β”œβ”€β”€ COCO2014/           
  β”‚   β”œβ”€β”€ annotations/
  β”‚   β”‚   β”œβ”€β”€ train2014/  # (dir.) training masks (from Google Drive) 
  β”‚   β”‚   β”œβ”€β”€ val2014/    # (dir.) validation masks (from Google Drive)
  β”‚   β”‚   └── ..some json files..
  β”‚   β”œβ”€β”€ train2014/
  β”‚   └── val2014/
  └── IC-VOS/
      β”œβ”€β”€ 0a43a414/
      β”‚   β”œβ”€β”€ Annotations/
      β”‚   └── JPEGImages/
      └── ...

Citation

@article{qi2025dc,
  title={DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency},
  author={Qi, Mengshi and Zhu, Pengfei and Ma, Huadong and Qi, Lu and Li, Xiangtai and Yang, Ming-Hsuan},
  journal={arXiv preprint arXiv:2504.12080},
  year={2025}
}
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