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RefRef: A Synthetic Dataset and Benchmark for Reconstructing Scenes with Refractive and Reflective Objects (haven't uploaded everything yet)

Overview

RefRef is a synthetic dataset and benchmark designed for the task of reconstructing scenes with complex refractive and reflective objects. Our dataset consists of 50 objects categorized based on their geometric and material complexity: single-material convex objects, single-material non-convex objects, and multi-material non-convex objects, where the materials have different colors, opacities, and refractive indices. Each object is placed in two distinct bounded environments and one unbounded environment, resulting in 150 unique scenes with diverse geometries, material properties, and backgrounds. Our dataset provides a controlled setting for evaluating and developing 3D reconstruction and novel view synthesis methods that handle complex optical effects.

Directory Structure

RefRef_Dataset/
β”œβ”€β”€ README.md
β”œβ”€β”€ dataset_info/                 # Metadata and dataset description files
β”‚   β”œβ”€β”€ object_list.txt
β”‚   β”œβ”€β”€ scene_list.txt
β”‚   └── IoR_info.json             # IoR values mapped to each object
β”œβ”€β”€ image_data/                   # Rendered images, depth maps, and masks for each object
β”‚   β”œβ”€β”€ textured_cube_scene/
β”‚   β”‚   └── {single-material_convex, single-material_non-convex, multiple-materials_non-convex}/
β”‚   β”‚       └── {object_name}/
β”‚   β”‚           β”œβ”€β”€ train/        # Training set
β”‚   β”‚           β”‚   β”œβ”€β”€ r_0.png              # RGB image
β”‚   β”‚           β”‚   β”œβ”€β”€ r_0_depth_0000.png   # Depth map
β”‚   β”‚           β”‚   β”œβ”€β”€ r_0_mask_0000.png    # Mask
β”‚   β”‚           β”‚   β”œβ”€β”€ r_1.png
β”‚   β”‚           β”‚   β”œβ”€β”€ r_1_depth_0000.png
β”‚   β”‚           β”‚   β”œβ”€β”€ r_1_mask_0000.png
β”‚   β”‚           β”‚   └── ...
β”‚   β”‚           β”œβ”€β”€ val/          # Validation set
β”‚   β”‚           β”œβ”€β”€ test/         # Testing set
β”‚   β”‚           β”œβ”€β”€ transforms_train.json
β”‚   β”‚           β”œβ”€β”€ transforms_val.json
β”‚   β”‚           └── transforms_test.json
β”‚   β”œβ”€β”€ textured_sphere_scene/
β”‚   β”‚   └── ...
β”‚   β”œβ”€β”€ environment_map_scene/
β”‚       └── ...
β”œβ”€β”€ mesh_files/                   # 3D mesh files (.ply format) for each object
β”‚   └── {single-material_convex, single-material_non-convex, multiple-materials_non-convex}/
β”‚       └── ...
β”œβ”€β”€ blender_files/                # Blender source files for each object, organised by scene
β”‚   β”œβ”€β”€ bgpanels_cube/            # Background panels for cube scene
β”‚   β”œβ”€β”€ bgpanels_sphere/          # Background panels for sphere scene
β”‚   └── {textured_cube_scene, textured_sphere_scene}/
β”‚       └── ...
└── benchmarks/                   # Benchmark results from various methods
    β”œβ”€β”€ oracle_method/
    β”œβ”€β”€ Zip-NeRF/
    β”œβ”€β”€ Ray Deformation/
    β”œβ”€β”€ MS-NeRF/
    β”œβ”€β”€ NeUS/
    └── ...

Object and Scenes

The dataset includes 50 objects categorised into four groups based on their complexity, material composition, and shape:

  • single-convex/(18 scenes): Objects with convex geometries, each composed of a single refractive material, such as transparent cubes, balls, and pyramids.
  • single-non-convex/(40 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.
  • multiple-non-convex/(42 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.

Each object is placed in two distinct scenes:

  • textured_cube_scene/: Objects placed within a bounded textured cube environment.
  • textured_sphere_scene/: Objects placed within a bounded textured sphere environment.
  • environment_map_scene/: Objects placed in an unbounded environment map background.

IoR Information

A single JSON file IoR_info.json is be provided in the dataset_info/ directory, which maps each component of each object to its Index of Refraction (IoR) values.

Example format for IoR_info.json:

{
  "cube": 1.5,
  "diamond": 2.418,
  "wine_glass": {"glass": 1.5, "alcohol": 1.36},
  "water_pitcher": {"glass": 1.5, "water": 1.333, "ice": 1.309}
  ...
}
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