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End of preview.
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.tarDownload 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.zipDownload 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/
├── VOC2012/ # PASCAL VOC2012 devkit
│ ├── Annotations/
│ ├── ImageSets/
│ ├── ...
│ └── SegmentationClassAug/
├── COCO2014/
│ ├── annotations/
│ │ ├── train2014/ # (dir.) training masks (from Google Drive)
│ │ ├── val2014/ # (dir.) validation masks (from Google Drive)
│ │ └── ..some json files..
│ ├── train2014/
│ └── val2014/
└── IC-VOS/
├── 0a43a414/
│ ├── Annotations/
│ └── 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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