# Dance Style Transfer with Cross-modal Transformer

arXiv: https://arxiv.org/abs/2208.09406 · HTML: https://mlsanity.com/paper/2208.09406/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 48 references that are in the map.
- First posted on arXiv 19 Aug 2022.

## Builds on (most cited first, 16 of 16)

- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization](https://mlsanity.com/paper/1703.06868/) (2017)
- [StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation](https://mlsanity.com/paper/1711.09020/) (2017)
- [Language Modeling with Gated Convolutional Networks](https://mlsanity.com/paper/1612.08083/) (2016)
- [AI Choreographer: Music Conditioned 3D Dance Generation with AIST++](https://mlsanity.com/paper/2101.08779/) (2021)
- [Style Transfer in Text: Exploration and Evaluation](https://mlsanity.com/paper/1711.06861/) (2017)
- [Deep representation learning for human motion prediction and classification](https://mlsanity.com/paper/1702.07486/) (2017)
- [Unpaired Motion Style Transfer from Video to Animation](https://mlsanity.com/paper/2005.05751/) (2020)
- [Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation](https://mlsanity.com/paper/1905.05621/) (2019)
- [Real-Time Style Modelling of Human Locomotion via Feature-Wise Transformations and Local Motion Phases](https://mlsanity.com/paper/2201.04439/) (2022)
- [CycleGAN-VC2: Improved CycleGAN-based Non-parallel Voice Conversion](https://mlsanity.com/paper/1904.04631/) (2019)
- [Parallel-Data-Free Voice Conversion Using Cycle-Consistent Adversarial Networks](https://mlsanity.com/paper/1711.11293/) (2017)
- [Symbolic Music Genre Transfer with CycleGAN](https://mlsanity.com/paper/1809.07575/) (2018)
- [Transflower: probabilistic autoregressive dance generation with multimodal attention](https://mlsanity.com/paper/2106.13871/) (2021)
- [Graph-based Normalizing Flow for Human Motion Generation and Reconstruction](https://mlsanity.com/paper/2104.03020/) (2021)
- [CycleTransGAN-EVC: A CycleGAN-based Emotional Voice Conversion Model with Transformer](https://mlsanity.com/paper/2111.15159/) (2021)

## Built on by (most cited first, 20 of 20)

- [EDGE: Editable Dance Generation From Music](https://mlsanity.com/paper/2211.10658/) (2022)
- [Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion Models](https://mlsanity.com/paper/2211.09707/) (2022)
- [Iterative Motion Editing with Natural Language](https://mlsanity.com/paper/2312.11538/) (2023)
- [Music-Driven Group Choreography](https://mlsanity.com/paper/2303.12337/) (2023)
- [Videoshop: Localized Semantic Video Editing with Noise-Extrapolated Diffusion Inversion](https://mlsanity.com/paper/2403.14617/) (2024)
- [SimMotionEdit: Text-Based Human Motion Editing with Motion Similarity Prediction](https://mlsanity.com/paper/2503.18211/) (2025)
- [RSMT: Real-time Stylized Motion Transition for Characters](https://mlsanity.com/paper/2306.11970/) (2023)
- [Controllable Group Choreography using Contrastive Diffusion](https://mlsanity.com/paper/2310.18986/) (2023)
- [Structured Multi-Track Accompaniment Arrangement via Style Prior Modelling](https://mlsanity.com/paper/2310.16334/) (2023)
- [Pose-to-Motion: Cross-Domain Motion Retargeting with Pose Prior](https://mlsanity.com/paper/2310.20249/) (2023)
- [GAITGen: Disentangled Motion-Pathology Impaired Gait Generative Model -- Bringing Motion Generation to the Clinical Domain](https://mlsanity.com/paper/2503.22397/) (2025)
- [Spatial and Modal Optimal Transport for Fast Cross-Modal MRI Reconstruction](https://mlsanity.com/paper/2305.02774/) (2023)
- [Omni-Supervised Motion Editing: Balancing Change and Invariance through Positive-Negative Learning](https://mlsanity.com/paper/2605.30969/) (2026)
- [Scalable Motion Style Transfer with Constrained Diffusion Generation](https://mlsanity.com/paper/2312.07311/) (2023)
- [Scalable Group Choreography via Variational Phase Manifold Learning](https://mlsanity.com/paper/2407.18839/) (2024)
- [Controllable Motion Synthesis and Reconstruction with Autoregressive Diffusion Models](https://mlsanity.com/paper/2304.04681/) (2023)
- [Dance Generation by Sound Symbolic Words](https://mlsanity.com/paper/2306.03646/) (2023)
- [ST-GDance: Long-Term and Collision-Free Group Choreography from Music](https://mlsanity.com/paper/2507.21518/) (2025)
- [Spatial Temporal Synergy: Balancing Change and Invariance in Text Driven 3D Human Motion Editing](https://mlsanity.com/paper/2608.16008/) (2026)
- [ST-GDance++: A Scalable Spatial-Temporal Diffusion for Long-Duration Group Choreography](https://mlsanity.com/paper/2603.22316/) (2026)

## Abstract (arXiv)

We present CycleDance, a dance style transfer system to transform an existing motion clip in one dance style to a motion clip in another dance style while attempting to preserve motion context of the dance. Our method extends an existing CycleGAN architecture for modeling audio sequences and integrates multimodal transformer encoders to account for music context. We adopt sequence length-based curriculum learning to stabilize training. Our approach captures rich and long-term intra-relations between motion frames, which is a common challenge in motion transfer and synthesis work. We further introduce new metrics for gauging transfer strength and content preservation in the context of dance movements. We perform an extensive ablation study as well as a human study including 30 participants with 5 or more years of dance experience. The results demonstrate that CycleDance generates realistic movements with the target style, significantly outperforming the baseline CycleGAN on naturalness, transfer strength, and content preservation.