pretty_name: SceneFly
license: apache-2.0
language:
- en
- zh
tags:
- video
- computer-vision
- world-model
- multimodal
- camera-pose
CaR
Compression and Retrieval: Implicit Memory Retrieval for Video World Models
Zhan Peng1,2, Jie Ma2, Huiqiang Sun1, Chong Gao2,3, Zhijie Xue1, Zhiyu Pan1, Zhiguo Cao1*, Jun Liang2*, Jing Li2
1Huazhong University of Science and Technology 2HUJING Digital Media & Entertainment Group 3Sun Yat-sen University
*Corresponding author
SceneFly
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.
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.
Usage
The dataset is provided as a split tar.gz stream. Merge the split parts and extract the dataset with:
cat SceneFly_* | tar -xzvf -
The split parts are named:
SceneFly_aa
SceneFly_ab
SceneFly_ac
...
After extraction, the dataset root will be:
SceneFly/
A checksum manifest is provided in:
manifest.csv
It records each split part name, part size, source dataset size, and SHA256 checksum.
Dataset Structure
SceneFly/
├── metadata.csv
├── AlbertMansion/
│ ├── 0/
│ │ ├── video.mp4
│ │ ├── camera.json
│ │ ├── prompt.txt
│ │ └── samples/
│ │ ├── sample000.json
│ │ ├── sample001.json
│ │ └── ...
│ ├── 1/
│ │ └── ...
│ └── ...
├── AsianArchitecture/
│ └── ...
└── ...
File Description
video.mp4: rendered scene video.camera.json: camera trajectory and intrinsic annotation for the video.prompt.txt: text description/prompt of the scene.samples/sampleXXX.json: sample-level annotation file.metadata.csv: global metadata index for all samples.manifest.csv: archive-level checksum and size manifest.
Sample Annotation Fields
Each samples/sampleXXX.json contains fields such as:
scene_name: scene identifier.video_name: video identifier inside the scene.image_width,image_height: video resolution.focal_length: camera focal length.context_start_segment,context_end_segment: context segment range.context_length_segments: number of context segments.context_segments: list of context segment IDs.context_start_frame: starting frame of the context window.context_num_frames: number of context frames.gt_segment: ground-truth target segment.gt_start_frame: starting frame of the ground-truth segment.gt_num_frames: number of ground-truth frames.overlap_score,containment_score,final_score: sample matching scores.
Metadata
metadata.csv provides one row per sample and includes the relative sample path plus the context and ground-truth fields above.
Citation
If you find this dataset useful, please cite:
@article{peng2026car,
title={Compression and Retrieval: Implicit Memory Retrieval for Video World Models},
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},
journal={arXiv preprint arXiv:2606.23105},
year={2026}
}