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Co-authored-by: Blake S <bsnelling@users.noreply.huggingface.co>

data_summary_card.md

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+# Data Summary for microsoft_renderformer-v1.1-swin-large 
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+## 1. General information 
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+**1.0.1 Version of the Summary:** 1.0 
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+**1.0.2 Last update:** 16-Dec-2025 
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+## 1.1 Model Developer Identification 
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+**1.1.1 Model Developer name and contact details:** Microsoft Corporation at One Microsoft Way, Redmond, WA 98052. Tel: 425-882-8080 
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+## 1.2 Model Identification 
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+**1.2.1 Versioned model name(s):** RenderFormer-V1.1-Large 
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+**1.2.2 Model release date:** 30-May-2025 
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+## 1.3 Overall training data size and characteristics 
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+### 1.3.1 Size of dataset and characteristics 
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+**1.3.1.A Text training data size:** Not applicable 
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+**1.3.1.B Text training data content:** Not applicable 
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+**1.3.1.C Image training data size:** 1 million to 1 billion images 
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+**1.3.1.D Image training data content:** HDR rendered images of synthetic 3D scenes composed of triangle meshes from Objaverse objects placed in template environments, with varying materials, lighting (1–8 diffuse triangle lights), and camera viewpoints at 256×256 and 512×512 resolutions 
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+**1.3.1.E Audio training data size:** Not applicable. Audio data is not part of the training data 
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+**1.3.1.F Audio training data content:** Not applicable 
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+**1.3.1.G Video training data size:** Not applicable. Video data is not part of the training data 
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+**1.3.1.H Video training data content:** Not applicable 
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+**1.3.1.I Other training data size:** Scenes comprised of triangle meshes up to 4,096 triangles per scene during training. 
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+**1.3.1.J Other training data content:** Triangle mesh geometry and per-triangle reflectance parameters (diffuse albedo, specular albedo, roughness), per-vertex normals, and light source specifications for synthetic scenes derived from Objaverse objects and template walls 
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+**1.3.2 Latest date of data acquisition/collection for model training:** Dec 2024 
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+**1.3.3 Is data collection ongoing to update the model with new data collection after deployment?** There is no further training on this released model. 
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+**1.3.4 Date the training dataset was first used to train the model:**  
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+01-May-2024 
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+**1.3.5 Rationale or purpose of data selection:** Synthetic scenes built from objects within templated environments were used to cover diverse geometries, materials, lighting setups, and camera placements while remaining controllable for supervised training with reference renders. This supports learning a generalizable neural rendering pipeline for triangle meshes with global illumination 
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+## 2. List of data sources 
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+### 2.1 Publicly available datasets 
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+**2.1.1 Have you used publicly available datasets to train the model?** Yes 
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+## 2.2 Private non-publicly available datasets obtained from third parties 
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+### 2.2.1 Datasets commercially licensed by rights holders or their representatives  
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+**2.2.1.A Have you concluded transactional commercial licensing agreement(s) with rights holder(s) or with their representatives?** Not applicable 
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+### 2.2.2 Private datasets obtained from other third-parties 
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+**2.2.2.A Have you obtained private datasets from third parties that are not licensed as described in Section 2.2.1, such as data obtained from providers of private databases, or data intermediaries?**  
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+No. 
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+## 2.3 Personal Information 
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+**2.3.1 Was personal data used to train the model?**  
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+No. 
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+## 2.4 Synthetic data 
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+**2.4.1 Was any synthetic AI-generated data used to train the model?**  
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+No. 
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+## 3. Data processing aspects 
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+### 3.1 Respect of reservation of rights from text and data mining exception or limitation 
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+**3.1.1 Does this dataset include any data protected by copyright, trademark, or patent?** Microsoft follows all required regulations and laws for processing data protected by copyright, trademark, or patent 
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+## 3.2 Other information 
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+**3.2.1 Does the dataset include information about consumer groups without revealing individual consumer identities?** Microsoft follows all required regulations and laws for protecting consumer identities 
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+**3.2.2 Was the dataset cleaned or modified before model training?**  
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+No. 
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