
# Dataset Card for VIMA-Data

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
- [Dataset Structure](#dataset-structure)
- [Dataset Creation](#dataset-creation)
- [Additional Information](#additional-information)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)

## Dataset Description

- **Homepage:** https://vimalabs.github.io/
- **Repository:** https://github.com/vimalabs/VimaBench
- **Paper:** https://arxiv.org/abs/2210.03094

### Dataset Summary

This is the official dataset used to train general robot manipulation agents with multimodal prompts, as presented in [paper](https://arxiv.org/abs/2210.03094). It contains 650K trajectories for 13 tasks in [VIMA-Bench](https://github.com/vimalabs/VimaBench). All demonstrations are generated by oracles.

## Dataset Structure

Data are grouped into different tasks. Within each trajectory's folder, there are two folders `rgb_front` and `rgb_top`, and three files `obs.pkl`, `action.pkl`, and `trajectory.pkl`. RGB frames from a certain perspective are separately stored in corresponding folder. `obs.pkl` includes segmentation and state of end effector. `action.pkl` contains oracle actions. `trajectory.pkl` contains meta information such as elapsed steps, task information, and object information. Users can build their custom data piepline starting from here. More details and examples can be found [here](https://github.com/vimalabs/VimaBench#training-data).

## Dataset Creation

All demonstrations are generated by scripted oracles.

## Additional Information

### Licensing Information

This dataset is released under the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/legalcode) license.

### Citation Information

If you find our work useful, please consider citing us! 

```bibtex
@inproceedings{jiang2023vima,
  title     = {VIMA: General Robot Manipulation with Multimodal Prompts},
  author    = {Yunfan Jiang and Agrim Gupta and Zichen Zhang and Guanzhi Wang and Yongqiang Dou and Yanjun Chen and Li Fei-Fei and Anima Anandkumar and Yuke Zhu and Linxi Fan},
  booktitle = {Fortieth International Conference on Machine Learning},
  year      = {2023}
}
```
license:cc-by-4.0 arxiv:2210.03094 region:us
{"license": "cc-by-4.0"}
TAGS
#license-cc-by-4.0 #arxiv-2210.03094 #region-us 


# Dataset Card for VIMA-Data

## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
- Dataset Structure
- Dataset Creation
- Additional Information
  - Licensing Information
  - Citation Information

## Dataset Description

- Homepage: URL
- Repository: URL
- Paper: URL

### Dataset Summary

This is the official dataset used to train general robot manipulation agents with multimodal prompts, as presented in paper. It contains 650K trajectories for 13 tasks in VIMA-Bench. All demonstrations are generated by oracles.

## Dataset Structure

Data are grouped into different tasks. Within each trajectory's folder, there are two folders 'rgb_front' and 'rgb_top', and three files 'URL', 'URL', and 'URL'. RGB frames from a certain perspective are separately stored in corresponding folder. 'URL' includes segmentation and state of end effector. 'URL' contains oracle actions. 'URL' contains meta information such as elapsed steps, task information, and object information. Users can build their custom data piepline starting from here. More details and examples can be found here.

## Dataset Creation

All demonstrations are generated by scripted oracles.

## Additional Information

### Licensing Information

This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.



If you find our work useful, please consider citing us! 


# Dataset Card for VIMA-Data ## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
- Dataset Structure
- Dataset Creation
- Additional Information
  - Licensing Information
  - Citation Information ## Dataset Description

- Homepage: URL
- Repository: URL
- Paper: URL ### Dataset Summary

This is the official dataset used to train general robot manipulation agents with multimodal prompts, as presented in paper. It contains 650K trajectories for 13 tasks in VIMA-Bench. All demonstrations are generated by oracles. ## Dataset Structure

Data are grouped into different tasks. Within each trajectory's folder, there are two folders 'rgb_front' and 'rgb_top', and three files 'URL', 'URL', and 'URL'. RGB frames from a certain perspective are separately stored in corresponding folder. 'URL' includes segmentation and state of end effector. 'URL' contains oracle actions. 'URL' contains meta information such as elapsed steps, task information, and object information. Users can build their custom data piepline starting from here. More details and examples can be found here. ## Dataset Creation

All demonstrations are generated by scripted oracles. ## Additional Information ### Licensing Information

This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.



If you find our work useful, please consider citing us!
TAGS
#license-cc-by-4.0 #arxiv-2210.03094 #region-us 
 # Dataset Card for VIMA-Data ## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
- Dataset Structure
- Dataset Creation
- Additional Information
  - Licensing Information
  - Citation Information ## Dataset Description

- Homepage: URL
- Repository: URL
- Paper: URL ### Dataset Summary

This is the official dataset used to train general robot manipulation agents with multimodal prompts, as presented in paper. It contains 650K trajectories for 13 tasks in VIMA-Bench. All demonstrations are generated by oracles. ## Dataset Structure

Data are grouped into different tasks. Within each trajectory's folder, there are two folders 'rgb_front' and 'rgb_top', and three files 'URL', 'URL', and 'URL'. RGB frames from a certain perspective are separately stored in corresponding folder. 'URL' includes segmentation and state of end effector. 'URL' contains oracle actions. 'URL' contains meta information such as elapsed steps, task information, and object information. Users can build their custom data piepline starting from here. More details and examples can be found here. ## Dataset Creation

All demonstrations are generated by scripted oracles. ## Additional Information ### Licensing Information

This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.



If you find our work useful, please consider citing us!