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