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SK-VG

The official dataset of Advancing Visual Grounding with Scene Knowledge: Benchmark and Method.

Introduction

We introduce a challenging task that requires VG models to reason over (image, scene knowledge, query) triples and build a new dataset named SK-VG on top of real images through manual annotations. In SK-VG, the image content and referring expressions are not sufficient to ground the target objects, forcing the models to have a reasoning ability on the long-form scene knowledge.

image

An example

{
      "image_name": "3853.jpg",
      "knowledge": "The man on the far right of the image is Spider-Man Bruce. A spider is painted on his back. His enemy Brandon is floating in the air across from him, wearing sunglasses. Brandon's servant Tom is behind Brandon, holding a cane in his hand. Bruce comes to destroy them today.",
      "ref_exp": "Bruce's enemy Brandon",
      "bbox": {
        "x": 1063.1217116217117,
        "y": 385.6505161505161,
        "width": 430.26939726939736,
        "height": 705.6600066600066
      }
}

Data

You can download the dataset from Google Drive.

Citation

If you find this dataset helpful, please cite the paper below.

@inproceedings{chen2023advancing,
        title={Advancing Visual Grounding With Scene Knowledge: Benchmark and Method},
        author={Chen, Zhihong and Zhang, Ruifei and Song, Yibing and Wan, Xiang and Li, Guanbin},
        booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
        pages={15039--15049},
        year={2023}
}