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"name": "SysCON3D",
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"description": "SysCON3D is a deterministic benchmark bundle for stress-testing multi-view 3D reconstruction backbones and 3D consistency metrics. It contains Mip-NeRF 360 reference images, calibration split manifests, and materialized inconsistent image sets including cross-scene mixtures, one-outlier samples, identical-image samples, Gaussian noise, patched Gaussian corruptions, and small Gaussian perturbations of otherwise consistent views.",
"url": "https://huggingface.co/datasets/syscon3d-neurips26/syscon3d",
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"Coverage is limited to nine static Mip-NeRF 360 scenes, deterministic image corruptions, fixed view counts, and 224x224 materialized stress-test images. Results may not generalize to dynamic scenes, human-centered scenes, outdoor-only or indoor-only deployment domains, or non-photographic imagery."
],
"rai:dataBiases": [
"The source scenes inherit the selection biases of Mip-NeRF 360, including a small number of mostly static real-world scenes and specific camera trajectories.",
"The inconsistent samples intentionally over-represent synthetic and adversarial stress cases such as cross-scene mixtures and Gaussian corruptions; these samples are not representative of naturally occurring multi-view captures."
],
"rai:personalSensitiveInformation": "The benchmark is based on public scene photographs and does not intentionally collect personal or sensitive attributes. It may still contain incidental real-world background content inherited from the source images.",
"rai:dataUseCases": [
"Recommended: evaluating robustness and abstention behavior of multi-view 3D reconstruction backbones and 3D consistency metrics under controlled stress tests.",
"Not recommended: training production models, evaluating demographic fairness, evaluating semantic recognition, or making claims about safety outside the documented stress-test setting."
],
"rai:dataSocialImpact": "The benchmark can improve transparency around failure modes of learned 3D reconstruction backbones and metrics. Misuse risk includes overclaiming robustness beyond the documented scenes and perturbations or treating synthetic stress-test behavior as equivalent to real-world safety.",
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"rai:dataCollection": "Source photographs and camera metadata come from the Mip-NeRF 360 benchmark. SysCON3D selects referenced images and materializes deterministic stress-test samples from those sources plus synthetic image corruptions.",
"rai:dataPreprocessingProtocol": "The release uses referenced-only packaging, rewrites manifests to portable paths under mipnerf360/, and stores materialized stress-test PNGs at 224x224. Synthetic scene types are generated deterministically from recorded sample ids, seeds, source paths, and corruption parameters in mipnerf360_impossible_splits.json.",
"rai:dataAnnotationProtocol": "No human semantic labels are included. The manifests provide programmatic sample metadata such as sample id, scene type, view count, source scenes, source image paths, synthetic seeds, and corruption parameters.",
"rai:dataReleaseMaintenancePlan": "The anonymous review release is versioned by the manifest field version=6 and by the Hugging Face dataset commit. Future updates should increment the manifest version and preserve prior release artifacts when possible.",
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