Version V1

ConductorMotion100

Liu, Fan;Chen, De-Long;Zhou, Rui-Zhi;Yang, Sai;Xu, Feng

Description

This repository is the official implementation of “Self-Supervised Music-Motion Synchronization Learning for Music-Driven Conducting Motion Generation”, by Fan Liu, Delong Chen, Ruizhi Zhou, Sai Yang, and Feng Xu. This repository also provide the access to the ConductorMotion100 dataset, which consists of 100 hours of orchestral conductor motions and aligned music Mel spectrogram.The above figure gives a high-level illustration of the proposed two-stage approach. The contrastive learning and generative learning stage are bridged by transferring learned music and motion encoders, as noted in dotted lines. Our approach can generate plausible, diverse, and music-synchronized conducting motion.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.7

FAIR Score

69%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Science Data Bank

License

Assigned Domain

Subfield

Artificial Intelligence

Field

Computer Science

Domain

Physical Sciences

Confidence Score

65%

Source

Open Alex

Keywords

Computer science and technologyself-supervised learninggenerative adversarial networkhuman motion generation

Normalization Factors

FT

57.69

CTw

1.00

MTw

1.00