Datasets:
Rewrite dataset card and keep one default config
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README.md
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pretty_name: Diffusion4D Animated
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language:
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- en
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tags:
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data_files:
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- split: train
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path: data/train-*.parquet
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- config_name: preview_sample
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data_files:
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- split: train
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path: preview_sample/train-*.parquet
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- config_name: with_previews
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data_files:
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- split: train
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path: with_previews/train-*.parquet
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- config_name: video_sample
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data_files:
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- split: train
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path: video_sample/train-*.parquet
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- config_name: with_media
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data_files:
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- split: train
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path: with_media/train-*.parquet
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---
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# Diffusion4D Animated
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irrelevant, technically invalid, duplicated by appearance, or difficult to
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import.
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##
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- `metadata/assets.parquet`: metadata snapshot used by the release tooling.
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- `metadata/assets.jsonl`: lossless JSONL mirror of the table.
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- `metadata/summary.json`: release coverage counts.
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frames, skinning weights, and a detected image texture. It is a technical flag,
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not a semantic quality label.
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`annotation_status` before use.
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## Provenance And
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The records originate from Diffusion4D
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##
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duplicate groups, and curated training subsets while retaining this raw index.
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---
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pretty_name: Diffusion4D Animated Assets
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language:
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- en
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tags:
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data_files:
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- split: train
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path: data/train-*.parquet
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---
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# Diffusion4D Animated Assets
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This dataset provides animated 3D assets referenced by Diffusion4D and
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Objaverse-XL in a directly browsable format. The default split contains 67,988
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rows. Each row includes metadata, a preview image, and a short preview video so
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that assets can be inspected in the Hugging Face Data Studio without first
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downloading the original 3D file.
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The repository also mirrors available raw assets and keeps their original
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source links and hashes. The current release is intentionally broad and may
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contain broken, static, duplicated, or semantically irrelevant assets.
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## Curation In Progress
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Our goal is to identify high-quality skeletal animations suitable for training
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and evaluating motion and 3D understanding models. We are currently annotating
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every asset with Qwen3-VL-30B-A3B-Instruct using four frames sampled from its
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animation.
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The automatic annotations include:
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- a broad semantic class and a more specific object class;
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- a short object description;
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- a description of the visible motion;
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- whether meaningful animation is visible and its strength;
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- visual quality, visible defects, and model confidence.
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These labels are machine generated and should not be treated as human-verified
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ground truth. Failed or malformed model responses will be processed again in a
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separate repair pass.
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## Planned Animated Subset
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We plan to publish a separate curated subset of animated animals, humanoids,
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robots, and other articulated characters. Selection will combine technical
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metadata, visual inspection, and Qwen annotations.
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For this subset we also plan to provide:
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- renders from multiple camera angles;
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- per-frame DINO visual features;
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- data arranged for training models such as MocapAnything v2.
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## Data Fields
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The table includes identifiers and source metadata, file format and hashes,
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animation and skeleton statistics when available, technical inspection flags,
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and embedded preview media. Additional Qwen annotation columns will be added
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after the full annotation and validation passes finish.
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Use availability and quality fields when filtering. A row being present does
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not mean that its raw asset is valid, complete, or suitable for training.
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## Provenance And Licensing
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The records and official renders originate from Diffusion4D and Objaverse-XL.
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Raw assets come from many upstream repositories and do not share a single
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normalized license. Source URLs are retained where available. Users are
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responsible for checking the license of each upstream asset before
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redistribution or commercial use. This dataset does not relicense third-party
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content.
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## Acknowledgements
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Please cite the original Diffusion4D and Objaverse-XL projects when using this
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dataset. This repository is an independent packaging and curation effort.
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