Motion Capture Dataset for Practical Use of AI-based Motion Editing and Stylization
This provides a practical dataset for researchers and industry professionals working on motion style transfer, though it is incremental as it builds on existing methods by offering new data.
The authors tackled the lack of industry-ready motion data for AI-based motion editing and stylization by proposing a new style-diverse dataset that uses an industrial-standard human bone structure, and results from experiments with state-of-the-art methods validated its effectiveness for motion style transfer tasks.
In this work, we proposed a new style-diverse dataset for the domain of motion style transfer. The motion dataset uses an industrial-standard human bone structure and thus is industry-ready to be plugged into 3D characters for many projects. We claim the challenges in motion style transfer and encourage future work in this domain by releasing the proposed motion dataset both to the public and the market. We conduct a comprehensive study on motion style transfer in the experiment using the state-of-the-art method, and the results show the proposed dataset's validity for the motion style transfer task.