--- title: ABot-World-Explorer-500h canonical_url: "https://www.modelscope.cn/datasets/amap_cvlab/ABot-World-Explorer-500h" md_url: "https://www.modelscope.cn/datasets/amap_cvlab/ABot-World-Explorer-500h.md" repository: amap_cvlab/ABot-World-Explorer-500h last_updated: 2026-08-06 license: apache-2.0 storage_size: "2.5 TB" downloads: 1200610 stars: 2 --- # ABot-World-Explorer-500h > ABot-World-Explorer-500h - amap_cvlab 在 ModelScope 开源的数据集。ABot World Explorer 500h amap_cvlab/ABot-World-Explorer-500h 是 ModelScope 魔搭社区上的数据集，存储大小 2.5 TB，采用 apache-2.0 许可。 - **Repository**: amap_cvlab/ABot-World-Explorer-500h - **License**: apache-2.0 - **Storage size**: 2.5 TB - **Downloads**: 1200610 - **Stars**: 2 - **Last updated**: 2026-08-06 Source: https://www.modelscope.cn/datasets/amap_cvlab/ABot-World-Explorer-500h --- # ABot World Explorer 500h [![Studio](https://img.shields.io/badge/Studio-ABot_World_Studio-green?logo=data:image/svg+xml;base64,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)](https://abot-world.amap.com) [![Playground](https://img.shields.io/badge/Reactor-ABot_World-E9E4C2?logo=data:image/svg+xml;base64,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)](https://reactor.inc/abot-world) [![Project](https://img.shields.io/badge/🌐_Project-ABot_World-blue)](https://amap-cvlab.github.io/ABot-World/) [![Paper](https://img.shields.io/badge/Paper-arXiv-red?logo=arxiv)](https://arxiv.org/abs/2607.19191) [![Code](https://img.shields.io/badge/Code-GitHub-181717?logo=github)](https://github.com/amap-cvlab/ABot-World) [![Model](https://img.shields.io/badge/Model-HuggingFace-yellow?logo=huggingface)](https://huggingface.co/acvlab/ABot-World-0-5B-LF) [![Space](https://img.shields.io/badge/Space-HuggingFace-yellow?logo=huggingface)](https://huggingface.co/spaces/acvlab/abot-world-interactive) [![Dataset](https://img.shields.io/badge/Dataset_500H-HuggingFace-yellow?logo=huggingface)](https://huggingface.co/datasets/acvlab/ABot-World-Explorer-500h) [![Dataset](https://img.shields.io/badge/Dataset_4D-HuggingFace-yellow?logo=huggingface)](https://huggingface.co/datasets/acvlab/ABot-World-Explorer-4D) [![Paper](https://img.shields.io/badge/Paper-HuggingFace-yellow?logo=huggingface)](https://huggingface.co/papers/2607.19191) [![Model](https://img.shields.io/badge/Model-ModelScope-7061FF?logo=modelscope)](https://modelscope.cn/models/amap_cvlab/ABot-World-0-5B-LF) [![Model](https://img.shields.io/badge/Space-ModelScope-7061FF?logo=modelscope)](https://modelscope.cn/studios/amap_cvlab/abot-world-0) [![Dataset](https://img.shields.io/badge/Dataset_500H-ModelScope-7061FF?logo=modelscope)](https://modelscope.cn/datasets/amap_cvlab/ABot-World-Explorer-500h) [![Dataset](https://img.shields.io/badge/Dataset_4D-ModelScope-7061FF?logo=modelscope)](https://modelscope.cn/datasets/amap_cvlab/ABot-World-Explorer-4D) ![ABot World Explorer data infrastructure](meta/abot-world-explorer-poster.png) ABot World Explorer 500h contains 30,969 action-conditioned video episodes associated with the data infrastructure described in [ABot-World-0](https://arxiv.org/abs/2607.19191). Each episode preserves an MP4, dataset-native keyboard actions, captions, and one COLMAP text sparse model. ## Dataset facts | Item | Value | |---|---:| | Episodes | 30,969 | | Source objects | 185,814 | | Semantic splits | None | | License | Apache-2.0 | The repository name is an identifier, not an audited duration claim. Exact duration, FPS, frame count, and alignment statistics belong to the complete release metadata. ## Layout ```text meta/abot-world-explorer-poster.png metadata.jsonl data///video.mp4 data///annotations.tar LICENSE README.md ``` `sample_id` is an anonymous HMAC identifier. `annotations.tar` is deterministic, uncompressed POSIX USTAR containing `action.json`, `caption.json`, and the complete `sparse/0/{cameras,images,points3D}.txt` COLMAP model. Source keys and OSS locations are not released. ## Preview The ModelScope **Preview** tab is backed by `metadata.jsonl`. It covers all 30,969 episodes and contains only each anonymous `sample_id` plus authenticated, commit-pinned links to the existing `video.mp4` and `annotations.tar` objects. It does not copy, rewrite, summarize, or otherwise modify captions, actions, or media payloads. ## Data file formats ### `video.mp4` and `annotations.tar` `video.mp4` preserves the source MP4 bytes without release-time transcoding. `annotations.tar` is an uncompressed POSIX USTAR archive. Treat its five members as one sample-level annotation package and validate their paths and hashes before extracting them. ### `action.json` `action.json` is a UTF-8 JSON object containing sequence metadata and a `frames` array. The released records use the following structure; the available controls and dataset-native numeric values may vary by sequence. | Field | JSON type | Description | |---|---|---| | `control_scheme` | string | Name of the source control convention. | | `original_fps`, `fps` | number | Source and sampled frame rates. | | `sample_stride` | integer | Sampling stride relative to the source sequence. | | `start_frame_index`, `end_frame_index`, `total_frames` | integer | Sequence/frame-range metadata. | | `thresholds` | object | Schema-specific control thresholds; it may be empty. | | `frames` | array of objects | One ordered control record per sampled frame. | Each `frames[]` object contains `frame_id` (string), `timestamp` (number), a `keys` mapping from control names to booleans, and four length-3 numeric vectors: `delta_translation_cam`, `delta_translation_cam_smooth`, `delta_euler_deg`, and `delta_euler_deg_smooth`. Rotation deltas are named in degrees; do not infer the translation or timestamp units, thresholds, or exact cross-modal alignment when the released schema metadata marks them as unknown. Some source variants add per-frame translation/rotation threshold and release fields. Readers should accept additional fields and must not assume a fixed set of keys. ### `caption.json` `caption.json` is a UTF-8 JSON object with `perspective`, `scene_static`, and `narrative` strings plus a `dense_temporal` array. `dense_temporal` may be empty; all current audit canaries contain an empty array, so its item schema is not claimed here. Consumers must not assume at least one segment. String values are preserved except that complete-token private source path identifiers are replaced with `[redacted]`; all other JSON values are preserved, and JSON keys are never rewritten. ### COLMAP pose files The three files under `sparse/0/` form one [COLMAP text sparse model](https://colmap.github.io/format.html#text-format) and must be interpreted together. Lines beginning with `#` are comments. - `cameras.txt`: one camera per line as `CAMERA_ID MODEL WIDTH HEIGHT PARAMS[]`. The parameter list depends on the [camera model](https://colmap.github.io/cameras.html). - `images.txt`: two lines per image. The first is `IMAGE_ID QW QX QY QZ TX TY TZ CAMERA_ID NAME`; the second is a repeated list of `(X, Y, POINT3D_ID)` observations and may be empty. The pose maps world coordinates to camera coordinates using a Hamilton quaternion. COLMAP camera axes are +X right, +Y down, +Z forward, and the camera center is `-R^T T`. - `points3D.txt`: one sparse point per line as `POINT3D_ID X Y Z R G B ERROR TRACK[]`; each track item is `(IMAGE_ID, POINT2D_IDX)`. A present but empty file is valid and means that the model contains no sparse 3D points. IDs are not guaranteed to be contiguous. See the official specifications for [`cameras.txt`](https://colmap.github.io/format.html#cameras-txt), [`images.txt`](https://colmap.github.io/format.html#images-txt), and [`points3D.txt`](https://colmap.github.io/format.html#points3d-txt). ## Selective download Use a full commit ID when reproducibility matters. The Preview index provides the anonymous `sample_id`; the two corresponding payload paths are derived from that ID without consulting source keys or OSS locations. ```python from modelscope_hub.api import HubApi REPO_ID = "amap_cvlab/ABot-World-Explorer-500h" REVISION = "" api = HubApi() sample_id = "" prefix = sample_id[:2] snapshot = api.download_repo( repo_id=REPO_ID, repo_type="dataset", revision=REVISION, allow_patterns=[ "LICENSE", "README.md", "metadata.jsonl", f"data/{prefix}/{sample_id}/video.mp4", f"data/{prefix}/{sample_id}/annotations.tar", ], ) print(snapshot) ``` Require exact regular-file member names before extracting TAR data. Plain `git clone` is not recommended for large payload download. ## Intended use and limitations Intended for research on action-conditioned video prediction, controllable world models, representation learning, and agent learning. It is not a symbolic simulator or a guarantee of physical or causal correctness. Users must assess suitability, bias, safety, and legal obligations for downstream use. ## Additional data access For additional data access or customized dataset requirements, please contact the AMAP Data Department directly at [phys_ai_data@service.alibaba.com](mailto:phys_ai_data@service.alibaba.com) ## Citation ```bibtex @misc{jiang2026abotworld0infiniteinteractiveworld, title={ABot-World-0: Infinite Interactive World Rollout on a Single Desktop GPU}, author={Fan Jiang and Zhaoxu Sun and Mengchao Wang and Ziyu Zhu and Chiyu Wang and Yunpeng Zhang and Wenlin Liu and Yun Wang and Xue Zheng and Rui Sun and Junfeng Ni and Hongyu Pan and Zhongxu Sun and Fei Yu and Zengye Ge and Mengmeng Du and Nianfei Fan and Mingchao Sun and Yu Liu and Yongchang and Yanqing Zhu and Jiahang Wang and Ning Ying and Yuze Xuan and Di Yang and Zhicheng Liu and Zhe Gao and Tingbing Xu and Jiacheng Sui and Wenjin Yang and Junnan Lai and Shufeng Liu and Yuan Liu and Zheng Zhou and Yingliang Peng and Dawei Cao and Kaifeng Sheng and Yuxiang Cai and Fei Lu and Mu Xu and Ning Guo}, year={2026}, eprint={2607.19191}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2607.19191}, } ```