| --- |
| license: cc-by-nc-sa-4.0 |
| language: |
| - en |
| pretty_name: SparseVideoNav Datasets |
| task_categories: |
| - robotics |
| - visual-question-answering |
| tags: |
| - embodied-ai |
| - vision-language-navigation |
| - robot-navigation |
| - video |
| - trajectory |
| - sparsevideonav |
| - opendrivelab |
| configs: |
| - config_name: bvn |
| data_files: |
| - split: train |
| path: bvn/data.jsonl |
| - config_name: ifn |
| data_files: |
| - split: train |
| path: ifn/data.jsonl |
| --- |
| |
| # SparseVideoNav Datasets |
|
|
|  |
|
|
| This repository contains the real-world navigation datasets released with [OpenDriveLab/SparseVideoNav](https://github.com/OpenDriveLab/SparseVideoNav): |
|
|
| - **BVN**: Beyond-the-View Navigation. |
| - **IFN**: Instruction-Following Navigation. |
|
|
| Project links: |
|
|
| - Project page: https://opendrivelab.com/SparseVideoNav |
| - GitHub: https://github.com/OpenDriveLab/SparseVideoNav |
| - Paper: https://arxiv.org/abs/2602.05827 |
|
|
| ## Dataset Summary |
|
|
| SparseVideoNav studies real-world vision-language navigation with sparse future video generation. The datasets contain language instructions, RGB frame sequences, and low-level navigation actions. The number of actions matches the number of RGB frames for every released episode. |
|
|
| Due to policy restrictions, this public release contains the policy-compliant subset of the collected real-world data. At the released sampling rate of **4 fps**, the open-sourced subset contains **about 100 hours** of navigation data. |
|
|
| | Subset | Episodes | RGB frames | Duration @ 4 fps | Task | |
| | --- | ---: | ---: | ---: | --- | |
| | `bvn` | 5,417 | 695,373 | 48.29 h | Beyond-the-View Navigation | |
| | `ifn` | 5,625 | 712,290 | 49.46 h | Instruction-Following Navigation | |
| | **Total** | **11,042** | **1,407,663** | **97.75 h** | - | |
|
|
| ## Repository Structure |
|
|
| Images are stored in compressed tar shards to avoid hundreds of thousands of small files in the Hugging Face repository. Each shard preserves the original relative paths. |
|
|
| ```text |
| . |
| ├── README.md |
| ├── assets/ |
| │ └── dataset_mosaic.png |
| ├── bvn/ |
| │ ├── annotations.json |
| │ ├── data.jsonl |
| │ ├── merge_info.json |
| │ ├── shard_manifest.jsonl |
| │ └── shards/ |
| │ ├── bvn-00000.tar.zst |
| │ └── ... |
| └── ifn/ |
| ├── annotations.json |
| ├── data.jsonl |
| ├── merge_info.json |
| ├── shard_manifest.jsonl |
| └── shards/ |
| ├── ifn-00000.tar.zst |
| └── ... |
| ``` |
|
|
| ## Data Format |
|
|
| Each line in `bvn/data.jsonl` or `ifn/data.jsonl` is an episode-level JSON object. |
|
|
| | Field | Type | Description | |
| | --- | --- | --- | |
| | `dataset` | string | Dataset subset name, either `bvn` or `ifn`. | |
| | `subset` | string | Release subset marker. The current public release uses `main`. | |
| | `episode_id` | string | Unique episode identifier. | |
| | `instruction` | string | Primary natural-language navigation instruction. | |
| | `instructions` | list[string] | Instruction list. Current records contain one instruction. | |
| | `task_type` | string | Task label, e.g. `beyond_the_view_navigation` or `instruction_following_navigation`. | |
| | `split` | string | Dataset split. Current release uses `train`. | |
| | `image_dir` | string | Original relative episode image directory before sharding. | |
| | `rgb_dir` | string | Original relative RGB frame directory. | |
| | `num_frames` | integer | Number of RGB frames in the episode. | |
| | `num_actions` | integer | Number of low-level actions. This matches `num_frames`. | |
| | `actions` | list[object] | Per-frame low-level navigation actions. Each action has `dx`, `dy`, and `dyaw`. | |
| | `annotation_file` | string | Annotation file path in this repository. | |
| | `frame_files` | list[string] | RGB frame paths inside the shard after extraction. | |
| | `asset_dirs` | list[string] | Original episode asset directories included in the shard. | |
| | `shard` | string | Tar shard containing the episode frames. | |
|
|
| Each action object contains: |
|
|
| | Field | Type | Description | |
| | --- | --- | --- | |
| | `dx` | float | Relative forward/backward displacement for the corresponding step. | |
| | `dy` | float | Relative lateral displacement for the corresponding step. | |
| | `dyaw` | float | Relative yaw change for the corresponding step. | |
|
|
| Example: |
|
|
| ```json |
| { |
| "dataset": "ifn", |
| "episode_id": "36e980e5a1ff4817", |
| "instruction": "please go along with the rail until you are near by a red cone.", |
| "num_frames": 177, |
| "num_actions": 177, |
| "rgb_dir": "images/0e0ec1bdcc61a4ef/rgb", |
| "frame_files": ["images/0e0ec1bdcc61a4ef/rgb/001.jpg"], |
| "shard": "ifn/shards/ifn-00000.tar.zst" |
| } |
| ``` |
|
|
| `annotations.json` stores the original annotation records with the core fields `id`, `video`, `actions`, and `instructions`. `shard_manifest.jsonl` stores shard-level metadata, including the shard path, episode ids, raw byte size, compressed byte size, frame count, and file count. |
|
|
| ## Usage |
|
|
| Load episode metadata with Hugging Face Datasets: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| bvn = load_dataset("OpenDriveLab/SparseVideoNav", "bvn") |
| ifn = load_dataset("OpenDriveLab/SparseVideoNav", "ifn") |
| ``` |
|
|
| Download and inspect shards: |
|
|
| ```bash |
| tar -I zstd -tf ifn/shards/ifn-00000.tar.zst | head |
| tar -I zstd -xf ifn/shards/ifn-00000.tar.zst |
| ``` |
|
|
| After extraction, `frame_files` resolve to paths such as: |
|
|
| ```text |
| images/<episode_dir>/rgb/001.jpg |
| ``` |
|
|
| ## License |
|
|
| The dataset is released under CC BY-NC-SA 4.0. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{zhang2026sparse, |
| title={Sparse Video Generation Propels Real-World Beyond-the-View Vision-Language Navigation}, |
| author={Zhang, Hai and Liang, Siqi and Chen, Li and Li, Yuxian and Xu, Yukuan and Zhong, Yichao and Zhang, Fu and Li, Hongyang}, |
| journal={arXiv preprint arXiv:2602.05827}, |
| year={2026} |
| } |
| ``` |
|
|
