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  A large-scale dataset for furniture understanding, featuring **photo-realistic rendered indoor scenes** with **high-quality 3D furniture models**. The dataset contains about 24k indoor images, 170k furniture instances, and 20k unique furniture identities, all rendered by the leading industry-level rendering engines in [Kujiale](https://coohom.com).
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  ## Key Features
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  - **Photo-Realistic Rendering**: All indoor scenes are rendered using professional rendering engines, providing realistic lighting, shadows, and textures
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  For benchmark details and baselines, please refer to our paper.
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- ## Paper
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- This dataset is introduced in our paper:
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- [Furnishing Your Room by What You See: An End-to-End Furniture Set Retrieval Framework with Rich Annotated Benchmark Dataset](https://arxiv.org/abs/1911.09299)
 
 
 
 
 
 
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  If you use this dataset, please cite:
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  ```bibtex
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  journal={arXiv preprint arXiv:1911.09299},
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  year={2020}
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  }
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- ```
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-
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- ## License
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- Apache-2.0
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-
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- ## Acknowledgments
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-
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- - Dataset created by [Kujiale](https://coohom.com)
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- - Rendered using the leading interior design platform in [Kujiale](https://coohom.com)
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- - Thanks to millions of designers and artists who contributed to the 3D models and designs
 
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  A large-scale dataset for furniture understanding, featuring **photo-realistic rendered indoor scenes** with **high-quality 3D furniture models**. The dataset contains about 24k indoor images, 170k furniture instances, and 20k unique furniture identities, all rendered by the leading industry-level rendering engines in [Kujiale](https://coohom.com).
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+ This dataset is introduced in our paper:
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+ [Furnishing Your Room by What You See: An End-to-End Furniture Set Retrieval Framework with Rich Annotated Benchmark Dataset](https://arxiv.org/abs/1911.09299)
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+
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  ## Key Features
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  - **Photo-Realistic Rendering**: All indoor scenes are rendered using professional rendering engines, providing realistic lighting, shadows, and textures
 
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  For benchmark details and baselines, please refer to our paper.
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+
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+ ## License
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+ Apache-2.0
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+
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+ ## Acknowledgments
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+
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+ - Dataset created by [Kujiale](https://coohom.com)
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+ - Rendered using the leading interior design platform in [Kujiale](https://coohom.com)
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+ - Thanks to millions of designers and artists who contributed to the 3D models and designs
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  If you use this dataset, please cite:
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  ```bibtex
 
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  journal={arXiv preprint arXiv:1911.09299},
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  year={2020}
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  }
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+ ```