| --- |
| license: cc-by-nc-sa-4.0 |
| language: |
| - en |
| pretty_name: "A Scaling Recipe for Generative World Renderer" |
| size_categories: |
| - 1M<n<10M |
| task_categories: |
| - video-classification |
| - image-to-image |
| - text-to-video |
| - other |
| tags: |
| - g-buffer |
| - inverse-rendering |
| - forward-rendering |
| - intrinsic-decomposition |
| - video |
| - benchmark |
| - synthetic |
| - games |
| - neurips-2026 |
| configs: |
| - config_name: sample |
| data_files: |
| - split: sample |
| path: "metadata.csv" |
| --- |
| |
| # A Scaling Recipe for Generative World Renderer |
|
|
| NeurIPS 2026 Evaluations & Datasets Track — anonymous submission. |
|
|
| > **Reviewer Sample — NeurIPS 2026 Submission.** |
| > This repository currently hosts a **40-clip flattened reviewer sample (≈ 2.8 GB)** so that NeurIPS 2026 reviewers can inspect data quality and format without per-request gated access. The full dataset described in the accompanying paper — approximately **4 M frames, 40 hours of playtime, 720p / 30 FPS, ~11 k sub-clips**, with five synchronized G-buffer channels (depth, normals, albedo, metallic, roughness) and a parallel motion-blurred RGB variant — totals roughly **2 TB** and therefore exceeds the 300 GB single-repository limit for public Hugging Face datasets. The complete release will be made publicly available via gated access by the NeurIPS 2026 camera-ready deadline, in compliance with the Datasets & Benchmarks public-release requirement. Anonymous access links to the full release will be provided in the supplementary material of the submission. The schema, license (CC BY-NC-SA 4.0), and Responsible-AI metadata (provided in the accompanying `croissant.json` at the repository root) apply identically to both the reviewer sample and the full release. |
|
|
| ## Schema (`sample` config) |
|
|
| | # | Column | Type | Description | |
| |---:|---|---|---| |
| | 1 | `game` | string | Source title: `cyberpunk2077` or `black_myth_wukong`. | |
| | 2 | `clip_id` | string | Stable identifier for the sub-clip. | |
| | 3 | `rgb_path` | string | Repo-relative path to the RGB video file. | |
| | 4 | `depth_path` | string | Repo-relative path to the depth G-buffer video file. | |
| | 5 | `normal_path` | string | Repo-relative path to the camera-space normals G-buffer video file. | |
| | 6 | `albedo_path` | string | Repo-relative path to the albedo / base-color G-buffer video file. | |
| | 7 | `metallic_path` | string | Repo-relative path to the metallic G-buffer video file. | |
| | 8 | `roughness_path` | string | Repo-relative path to the roughness G-buffer video file. | |
|
|
| ## Intended Use Cases |
|
|
| - Video inverse rendering (depth / normals / albedo / metallic / roughness from RGB). |
| - G-buffer-conditioned forward generative rendering and neural relighting. |
| - Controllable video editing of AAA-style game footage (style, lighting, weather, visual-effect transfer). |
| - Material-decomposition and intrinsic-image benchmarks on long, dynamic, in-the-wild-style sequences. |
| - Temporal-consistency research for video diffusion, video depth, and video normal estimators. |
| - Synthetic-to-real transfer and motion-blur robustness studies (paired sharp / blurred RGB). |
| - Development and benchmarking of VLM-as-judge protocols for material-channel quality assessment. |
|
|
| ## License |
|
|
| The dataset is released under the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International** license (**CC BY-NC-SA 4.0**), in accordance with each source game developer's Fan Content Policy and EULA, which permit non-commercial derivative works and sharing. |
|
|
| The full release is gated: researchers will be required to sign a Terms-of-Use agreement acknowledging the source-game copyrights and committing to non-commercial research use before access is granted. The toolkit used to curate the dataset will be open-sourced separately to enable reproducible extension to additional games. |
|
|
| ## Limitations |
|
|
| - Domain coverage is biased toward the two source titles' art directions; under-represents medical, microscopy, and aerial photometric phenomena. |
| - G-buffer extraction relies on offline RenderDoc inspection and per-title ReShade hooks; porting to a new game requires non-trivial engineering effort. |
| - Camera-space normals are reconstructed from the depth buffer via inverse projection and finite differences, which can introduce high-frequency noise on thin or aliased structures. |
| - The released VLM-based evaluation protocol is a complementary, not a replacement, signal to ground-truth metrics; it inherits the judge model's failure modes on ambiguous coated / painted metals, wet surfaces, translucency, and compression artifacts. |
|
|
| ## Ethics, Safeguards, and Broader Impact |
|
|
| - **No personal data.** All visual content is synthetic game-engine output. Any depicted humanoid figures are fictional in-game characters; no real-world faces, voices, geolocation, medical, demographic, political, religious, or socio-economic personal data are collected, derived, or distributed. |
| - **Misuse mitigation.** Potential misuse — generating manipulated or stylized game footage without attribution — is mitigated by (i) gated access with a signed Terms-of-Use restricting use to non-commercial research, (ii) the CC BY-NC-SA 4.0 license that propagates non-commercial and share-alike obligations to derivative works, and (iii) preservation of the original games' watermarks / HUDs in every captured frame so downstream re-renders remain identifiable as game-derived content. |
| - **User study.** A 25-expert pairwise preference user study was conducted as part of the accompanying paper. Participation was voluntary and uncompensated; no personally identifying information was collected. |
|
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|
