GENRE-CONDITIONED LONG-TERM 3D DANCE GENERATION DRIVEN BY MUSIC

Yuhang Huang, Junjie Zhang, Shuyan Liu, Qian Bao*, Dan Zeng*, Zhineng Chen, Wu Liu

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

10 Citations (Scopus)

Abstract

Dancing to music is an artistic behavior of humans, however, letting machines generate dances from music is still challenging. Most existing works have been made progress in tackling the problem of motion prediction conditioned by music, yet they rarely consider the importance of the musical genre. In this paper, we focus on generating long-term 3D dance from music with a specific genre. Specifically, we construct a pure transformer-based architecture to correlate motion features and music features. To utilize the genre information, we propose to embed the genre categories into the transformer decoder so that it can guide every frame. Moreover, different from previous inference schemes, we introduce the motion queries to output the dance sequence in parallel that significantly improves the efficiency. Extensive experiments on AIST++[1] dataset show that our model outperforms state-of-the-art methods with a much faster inference speed.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4858-4862
Number of pages5
ISBN (Electronic)9781665405409
DOIs
Publication statusPublished - 2022
Externally publishedYes
Event47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Virtual, Online, Singapore
Duration: 23 May 202227 May 2022

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2022-May
ISSN (Print)1520-6149

Conference

Conference47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
Country/TerritorySingapore
CityVirtual, Online
Period23/05/2227/05/22

Keywords

  • 3D dance generation
  • genre-conditioned
  • modality fusion
  • music-driven

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