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Enhance dataset card with task categories, tags, intro, and sample usage (#2)

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- Enhance dataset card with task categories, tags, intro, and sample usage (2f35fd24638695f74c0e286672e4391686252d2d)


Co-authored-by: Niels Rogge <[email protected]>

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  1. README.md +30 -1
README.md CHANGED
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  ---
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  license: cc-by-nc-4.0
 
 
 
 
 
 
 
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  ---
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  # SpatialGen Testset
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  [Project page](https://manycore-research.github.io/SpatialGen) | [Paper](https://arxiv.org/abs/2509.14981) | [Code](https://github.com/manycore-research/SpatialGen)
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  We provide a test set of 48 preprocessed point clouds and their corresponding GT layouts, multi-view images are cropped from the high-resolution panoramic images.
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  └── test_split_caption.jsonl # textural captions for each scene
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  ```
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- ## Visualization
 
 
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  We provide a [code](https://github.com/manycore-research/SpatialGen/blob/main/visualize_layout.py) to visualize the layout data.
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  # save layout_bbox.ply and camera poses in vis_output_dir
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  visualize_spatialgen_data(scene_data_dir, vis_output_dir)
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  ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: cc-by-nc-4.0
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+ task_categories:
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+ - image-to-3d
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+ - text-to-3d
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+ tags:
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+ - 3d
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+ - scene-generation
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+ - indoor-scenes
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  ---
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  # SpatialGen Testset
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+ This repository contains the test set for [SPATIALGEN: Layout-guided 3D Indoor Scene Generation](https://arxiv.org/abs/2509.14981), a novel multi-view multi-modal diffusion model for generating realistic and semantically consistent 3D indoor scenes.
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+
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  [Project page](https://manycore-research.github.io/SpatialGen) | [Paper](https://arxiv.org/abs/2509.14981) | [Code](https://github.com/manycore-research/SpatialGen)
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  We provide a test set of 48 preprocessed point clouds and their corresponding GT layouts, multi-view images are cropped from the high-resolution panoramic images.
 
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  └── test_split_caption.jsonl # textural captions for each scene
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  ```
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+ ## Sample Usage
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+
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+ ### Visualization
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  We provide a [code](https://github.com/manycore-research/SpatialGen/blob/main/visualize_layout.py) to visualize the layout data.
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  # save layout_bbox.ply and camera poses in vis_output_dir
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  visualize_spatialgen_data(scene_data_dir, vis_output_dir)
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  ```
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+
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+ ### Inference
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+
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+ This dataset is used for evaluating the SpatialGen models for 3D indoor scene generation. The following commands from the [code repository](https://github.com/manycore-research/SpatialGen) demonstrate how to run inference for different tasks (after following the installation instructions in the repository).
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+ **Single image-to-3D Scene Generation**
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+
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+ ```bash
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+ bash scripts/infer_spatialgen_i2s.sh
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+ ```
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+
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+ **Text-to-image-to-3D Scene Generation**
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+
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+ You can choose a pair of `scene_id` and `prompt` from `captions/spatialgen_testset_captions.jsonl` to run the text-to-scene experiment.
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+ ```bash
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+ bash scripts/infer_spatialgen_t2s.sh
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+ ```