MotionGPT- Human Motion as a Foreign Language

MotionGPT is a unified and user-friendly motion-language model designed to learn the semantic coupling between human motion and language. It has the capability to generate high-quality motions and text descriptions for multiple motion tasks.

Introduction

While there have been significant advancements in pre-trained large language models, the development of a unified model for language and other multi-modal data, such as motion, has remained a challenge. However, human motion exhibits a semantic coupling similar to human language, often referred to as body language. By combining language data with large-scale motion models, it becomes possible to enhance the performance of motion-related tasks through motion-language pre-training. Based on this insight, MotionGPT was developed as a versatile and user-friendly motion-language model capable of handling various motion-relevant tasks.

Description

MotionGPT employs discrete vector quantization to represent human motion and converts 3D motion into motion tokens, similar to the generation process of word tokens. This "motion vocabulary" allows for language modeling on both motion and text in a unified manner, treating human motion as a specific language. Additionally, inspired by prompt learning, MotionGPT is pre-trained with a mixture of motion-language data and fine-tuned on prompt-based question-and-answer tasks.

How Does It Work?

MotionGPT utilizes a two-step process to generate high-quality motions and text descriptions. First, it performs motion-language pre-training by learning the semantic coupling between human motion and language. This pre-training process enables the model to understand the relationship between motion tokens and their corresponding text descriptions. In the second step, MotionGPT fine-tunes on prompt-based question-and-answer tasks to further enhance its performance on motion-related tasks.

Benefits and Use Cases

MotionGPT offers several benefits and can be applied to various motion tasks. Some of the use cases include:

Text-Driven Motion Generation: MotionGPT can generate high-quality motions based on text descriptions. This can be useful in applications such as animation, virtual reality, and robotics, where generating realistic and expressive motions based on textual input is required.
Motion Captioning: MotionGPT can generate descriptive text captions for given motion sequences. This can be valuable in video analysis, motion understanding, and content generation, where providing textual descriptions of motion data is necessary.
Motion Prediction: MotionGPT can predict future motion sequences based on given input. This can be beneficial in applications such as sports analysis, motion planning, and human-computer interaction, where predicting future motions can assist in decision-making processes.
Motion In-Between: MotionGPT can generate intermediate motion sequences between two given motions. This can be useful in animation, character control, and motion editing, where smoothly transitioning between different motions is required.

Future Directions

The development of MotionGPT opens up several possibilities for future research and improvements. Some potential directions include:

Fine-tuning on specific motion tasks: MotionGPT can be further fine-tuned on specific motion tasks to improve its performance and adaptability to different domains.
Integration with real-time motion capture systems: Integrating MotionGPT with real-time motion capture systems can enable real-time generation and analysis of motions based on live input.
Multi-modal fusion: Exploring the fusion of additional modalities, such as audio or visual data, with motion and language can enhance the capabilities of MotionGPT and enable more diverse applications.

Conclusion

MotionGPT is a unified and user-friendly motion-language model that enables the generation of high-quality motions and text descriptions for multiple motion tasks. By leveraging the semantic coupling between human motion and language, MotionGPT opens up new possibilities for motion-related applications in various domains. With further research and development, MotionGPT has the potential to revolutionize the way we interact with and generate motions in fields such as animation, virtual reality, robotics, and more.