| ---
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| pretty_name: SceneFly
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| license: apache-2.0
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| language:
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| - en
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| - zh
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| tags:
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| - video
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| - computer-vision
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| - world-model
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| - multimodal
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| - camera-pose
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| ---
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|
|
| # CaR
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|
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| ## Compression and Retrieval: Implicit Memory Retrieval for Video World Models
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|
|
| <a href="https://pzzz-cv.github.io/">Zhan Peng</a><sup>1,2</sup>,
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| Jie Ma<sup>2</sup>,
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| Huiqiang Sun<sup>1</sup>,
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| Chong Gao<sup>2,3</sup>,
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| Zhijie Xue<sup>1</sup>,
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| Zhiyu Pan<sup>1</sup>,
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| Zhiguo Cao<sup>1*</sup>,
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| Jun Liang<sup>2*</sup>,
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| Jing Li<sup>2</sup>
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|
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| <sup>1</sup>Huazhong University of Science and Technology
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| <sup>2</sup>HUJING Digital Media & Entertainment Group
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| <sup>3</sup>Sun Yat-sen University
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|
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| <sup>*</sup>Corresponding author
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|
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| [](https://arxiv.org/abs/2606.23105)
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| [](https://orange-3dv-team.github.io/CaR/)
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| [](https://huggingface.co/datasets/Orange-3DV-Team/SceneFly)
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|
|
| ## SceneFly
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|
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| `SceneFly` is a curated video dataset organized by synthetic 3D scenes. Each selected video contains the source video, camera annotations, text prompt, and sample-level context/ground-truth metadata.
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|
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| This release contains a subset of the SceneFly dataset filter, including 58 scenes, 462 videos, and 45,173 sample annotations. The complete dataset will be provided in a future release.
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|
|
| ## Usage
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|
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| The dataset is provided as a split `tar.gz` stream. Merge the split parts and extract the dataset with:
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|
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| ```bash
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| cat SceneFly_* | tar -xzvf -
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| ```
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|
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| The split parts are named:
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|
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| ```text
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| SceneFly_aa
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| SceneFly_ab
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| SceneFly_ac
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| ...
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| ```
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|
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| After extraction, the dataset root will be:
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|
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| ```text
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| SceneFly/
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| ```
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|
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| A checksum manifest is provided in:
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|
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| ```text
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| manifest.csv
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| ```
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| It records each split part name, part size, source dataset size, and SHA256 checksum.
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|
|
| ## Dataset Structure
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|
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| ```text
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| SceneFly/
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| ├── metadata.csv
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| ├── AlbertMansion/
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| │ ├── 0/
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| │ │ ├── video.mp4
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| │ │ ├── camera.json
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| │ │ ├── prompt.txt
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| │ │ └── samples/
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| │ │ ├── sample000.json
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| │ │ ├── sample001.json
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| │ │ └── ...
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| │ ├── 1/
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| │ │ └── ...
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| │ └── ...
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| ├── AsianArchitecture/
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| │ └── ...
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| └── ...
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| ```
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|
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| ## File Description
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|
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| - `video.mp4`: rendered scene video.
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| - `camera.json`: camera trajectory and intrinsic annotation for the video.
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| - `prompt.txt`: text description/prompt of the scene.
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| - `samples/sampleXXX.json`: sample-level annotation file.
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| - `metadata.csv`: global metadata index for all samples.
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| - `manifest.csv`: archive-level checksum and size manifest.
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|
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| ## Sample Annotation Fields
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|
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| Each `samples/sampleXXX.json` contains fields such as:
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|
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| - `scene_name`: scene identifier.
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| - `video_name`: video identifier inside the scene.
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| - `image_width`, `image_height`: video resolution.
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| - `focal_length`: camera focal length.
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| - `context_start_segment`, `context_end_segment`: context segment range.
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| - `context_length_segments`: number of context segments.
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| - `context_segments`: list of context segment IDs.
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| - `context_start_frame`: starting frame of the context window.
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| - `context_num_frames`: number of context frames.
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| - `gt_segment`: ground-truth target segment.
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| - `gt_start_frame`: starting frame of the ground-truth segment.
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| - `gt_num_frames`: number of ground-truth frames.
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| - `overlap_score`, `containment_score`, `final_score`: sample matching scores.
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|
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| ## Metadata
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|
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| `metadata.csv` provides one row per sample and includes the relative sample path plus the context and ground-truth fields above.
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|
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| ## Citation
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|
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| If you find this dataset useful, please cite:
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|
|
| ```bibtex
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| @article{peng2026car,
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| title={Compression and Retrieval: Implicit Memory Retrieval for Video World Models},
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| author={Peng, Zhan and Ma, Jie and Sun, Huiqiang and Gao, Chong and Xue, Zhijie and Pan, Zhiyu and Cao, Zhiguo and Liang, Jun and Li, Jing},
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| journal={arXiv preprint arXiv:2606.23105},
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| year={2026}
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| }
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| ```
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|
|
