Datasets:
Tasks:
Image Segmentation
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
ArXiv:
Tags:
panorama
License:
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README.md
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license: apache-2.0
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task_categories:
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language:
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- en
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pretty_name: S2D3D
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size_categories:
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- 100M<n<1B
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---
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-
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This dataset originates from [S2D3D](https://github.com/alexsax/2D-3D-Semantics), propcessed by [360BEV](https://github.com/jamycheung/360BEV) and is used by our ECCV'24 paper [OPS](https://junweizheng93.github.io/publications/OPS/OPS.html).
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If you're interested in this dataset, please cite the following paper:
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```text
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@article{armeni2017joint,
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title={Joint 2d-3d-semantic data for indoor scene understanding},
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---
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license: apache-2.0
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task_categories:
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- image-segmentation
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language:
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- en
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pretty_name: S2D3D
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size_categories:
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- 100M<n<1B
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tags:
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- panorama
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---
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<div align="center" style="display: flex; align-items: center; justify-content: center; gap: 16px;">
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<div style="text-align: center;">
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<h1 style="margin: 0; font-size: 2em;">S2D3D Dataset</h1>
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<p style="margin: 6px 0 0; font-size: 1.2em;">A panoramic dataset for indoor semantic segmentation</p>
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</div>
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</div>
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## 📕 Introduction
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This dataset originates from [S2D3D](https://github.com/alexsax/2D-3D-Semantics), propcessed by [360BEV](https://github.com/jamycheung/360BEV) and is used by our ECCV'24 paper [OPS](https://junweizheng93.github.io/publications/OPS/OPS.html).
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If you're interested in this dataset, please cite the following paper:
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## 📖 Citation
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```text
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@article{armeni2017joint,
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title={Joint 2d-3d-semantic data for indoor scene understanding},
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