[ECCV2024] 🐙Octopus, an embodied vision-language model trained with RLEF, emerging superior in embodied visual planning and programming.
301
stars
36
commits
Python
primary language
May 20, 2024
updated
Project Page | Octopus Paper | Demo Video
Octopus is a novel VLM designed to proficiently decipher an agent’s vision and textual task objectives and to formulate intricate action sequences and generate executable code. We provide two models based on the following architectures. Please click
OctoVerse contains three sub-worlds
| OS (tested) | Environment Goal | |
|---|---|---|
| OctoGibson | Ubuntu 20.04 | 500 Tasks on OmniGibson |
| OctoGTA | Windows 11 | 20 Tasks to evaluate transfer learning |
| OctoMC | Ubuntu/Windows | 20 Tasks to evaluate transfer learning on MineCraft worlds, such as making an axe. |
octogibson environmentoctogibson environmentoctogta environmentoctopus modelContact: Leave issue or contact jingkang001@e.ntu.edu.sg and dongyh20@mails.tsinghua.edu.cn. We are on call to respond.
[2023-10]
octogibson environment, you need to set up two conda environments: omnigibson and gpt4. The omnigibson environment has an agent to act following the instruction from gpt4 environment. Please checkout here for detailed information.If you found this repository useful, please consider citing:
@article{yang2023octopus,
title = {Octopus: Embodied Vision-Language Programmer from Environmental Feedback},
author = {Jingkang Yang and Yuhao Dong and Shuai Liu and Bo Li and Ziyue Wang and Chencheng Jiang and Haoran Tan and Jiamu Kang and Yuanhan Zhang and Kaiyang Zhou and Ziwei Liu},
year = {2023},
}
We thank the OmniGibson team for their help and great contribution to the open-source community.
Python
93.0%
Shell
3.0%
JavaScript
2.9%
[ECCV2024] 🐙Octopus, an embodied vision-language model trained with RLEF, emerging superior in embodied visual planning and programming.
301
stars
36
commits
Python
primary language
May 20, 2024
updated
Project Page | Octopus Paper | Demo Video
Octopus is a novel VLM designed to proficiently decipher an agent’s vision and textual task objectives and to formulate intricate action sequences and generate executable code. We provide two models based on the following architectures. Please click
OctoVerse contains three sub-worlds
| OS (tested) | Environment Goal | |
|---|---|---|
| OctoGibson | Ubuntu 20.04 | 500 Tasks on OmniGibson |
| OctoGTA | Windows 11 | 20 Tasks to evaluate transfer learning |
| OctoMC | Ubuntu/Windows | 20 Tasks to evaluate transfer learning on MineCraft worlds, such as making an axe. |
octogibson environmentoctogibson environmentoctogta environmentoctopus modelContact: Leave issue or contact jingkang001@e.ntu.edu.sg and dongyh20@mails.tsinghua.edu.cn. We are on call to respond.
[2023-10]
octogibson environment, you need to set up two conda environments: omnigibson and gpt4. The omnigibson environment has an agent to act following the instruction from gpt4 environment. Please checkout here for detailed information.If you found this repository useful, please consider citing:
@article{yang2023octopus,
title = {Octopus: Embodied Vision-Language Programmer from Environmental Feedback},
author = {Jingkang Yang and Yuhao Dong and Shuai Liu and Bo Li and Ziyue Wang and Chencheng Jiang and Haoran Tan and Jiamu Kang and Yuanhan Zhang and Kaiyang Zhou and Ziwei Liu},
year = {2023},
}
We thank the OmniGibson team for their help and great contribution to the open-source community.
Python
93.0%
Shell
3.0%
JavaScript
2.9%