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--- |
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license: cc-by-nc-4.0 |
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task_category: image_to_3d |
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--- |
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This repository contains the `Remove360` dataset. |
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The `Remove360` dataset provides paired pre/post-removal RGB images and object-level masks captured in real-world indoor and outdoor environments. It is designed to benchmark and evaluate semantic residuals—unintended semantic traces left behind—after object removal in 3D Gaussian Splatting. The dataset covers a broader and more complex range of full-scene representations, enabling comprehensive evaluation of 3D object removal techniques beyond isolated object instances. |
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This dataset is intended to help assess whether semantic presence can truly be eliminated after object removal and if downstream models can still infer what was removed. |
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**License:** [CC-BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) |
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**Citing Remove360 Dataset:** |
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If you use Remove360 Dataset in your research, please cite it using the following BibTeX entry. |
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``` |
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@article{sam3dteam2025sam3d3dfyimages, |
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title={Remove360: Benchmarking Residuals After Object Removal in 3D Gaussian Splatting}, |
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author={Simona Kocour and Assia Benbihi and Torsten Sattler}, |
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year={2025}, |
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eprint={2508.11431}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2508.11431}, |
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} |
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``` |
