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README.md
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dataset_size: 673141617.0
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---
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##
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│ ├── scene_list.txt
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│ └── object_materials.json # IoR values mapped to each object
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├── image_data/ # Rendered images, depth maps, and masks for each object
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│ ├── textured_cube_scene/
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│ │ └── {single-material_convex, single-material_non-convex, multiple-materials_non-convex}/
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│ │ └── {object_name}/
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│ │ ├── train/ # Training set
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│ │ │ ├── r_0.png # RGB image
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│ │ │ ├── r_0_depth_0000.png # Depth map
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│ │ │ ├── r_0_mask_0000.png # Mask
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│ │ │ ├── r_1.png
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│ │ │ ├── r_1_depth_0000.png
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│ │ │ ├── r_1_mask_0000.png
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│ │ │ └── ...
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│ │ ├── val/ # Validation set
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│ │ ├── test/ # Testing set
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│ │ ├── transforms_train.json
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│ │ ├── transforms_val.json
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│ │ └── transforms_test.json
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│ ├── textured_sphere_scene/
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│ │ └── ...
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│ ├── environment_map_scene/
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│ └── ...
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└── mesh_files/ # 3D mesh files (.ply format) for each object
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└── {single-material_convex, single-material_non-convex, multiple-materials_non-convex}/
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└── ...
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```
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## Object and Scenes
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The dataset includes 50 objects categorised into four groups based on their complexity, material composition, and shape:
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- `single-convex/`(27 scenes): Objects with convex geometries, each composed of a single refractive material, such as transparent cubes, balls, and pyramids.
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- `single-non-convex/`(60 scenes): Objects with non-convex geometries, each composed of a single refractive material, such as animal sculptures, glass jars, light bulbs, candle holders, and magnifiers.
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- `multiple-non-convex/`(63 scenes): Objects with non-convex geometries, each composed of multiple refractive materials or a combination of refractive and opaque materials, such as reed diffusers, a glass of wine, and flasks filled with chemical liquid.
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Each object is placed in two distinct scenes:
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- `textured_cube_scene/`: Objects placed within a bounded textured cube environment.
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- `textured_sphere_scene/`: Objects placed within a bounded textured sphere environment.
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- `environment_map_scene/`: Objects placed in an unbounded environment map background.
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dataset_size: 673141617.0
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---
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## This repository provides additional data for: [RefRef: A Synthetic Dataset and Benchmark for Reconstructing Refractive and Reflective Objects](https://huggingface.co/datasets/yinyue27/RefRef)
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## Citation
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```
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@misc{yin2025refrefsyntheticdatasetbenchmark,
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title={RefRef: A Synthetic Dataset and Benchmark for Reconstructing Refractive and Reflective Objects},
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author={Yue Yin and Enze Tao and Weijian Deng and Dylan Campbell},
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year={2025},
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eprint={2505.05848},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2505.05848},
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}
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```
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