Datasets:
Modalities:
Image
Languages:
English
Size:
10K<n<100K
ArXiv:
Tags:
Spatial Intelligence
Depth Understanding
Vision Language Model
Multi-modal Large Language Model
License:
Dataset Preview
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End of preview.
SpatialQA enhances the model's spatial understanding capabilities by helping it comprehend and utilize depth maps.
In this HF dataset, SpatialQA.json
and high-level images are provided. Please also download images in Bunny_695k for low and middle-level images.
How to use this dataset
- Download images and json from this repo
- Download Bunny_695k
- Prepare depth map for coco_2017 and visual_genome. Please refer to our instructions.
- File structure:
/images
/images/coco_2017
/images/coco_2017_d
/images/visual_genome
/images/visual_genome_d
/images/visual_genome
/images/open_images
/images/ocrvqa
/images/2d3ds
/images/2d3ds_d
/images/kitti
/images/kitti_d
/images/nyudepthv2
/images/nyudepthv2_d
/images/sa1b # sa-1b is under sa1b-1.tar ~ sa1b4.tar in this repo
/images/sa1b_d
SpatialBot-3B
Our finetuned 3B model can be found at: https://huggingface.co/RussRobin/SpatialBot-3B
Paper:
https://arxiv.org/abs/2406.13642
GitHub repo:
https://github.com/BAAI-DCAI/SpatialBot
SpatialBot, a VLM with precise depth understanding:
https://huggingface.co/RussRobin/SpatialBot
SpatialBench, the spatial understanding benchmark:
- Downloads last month
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