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Dance2Music: Automatic Dance-driven Music Generation
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Dance2Music: Automatic Dance-driven Music Generation
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Dance and music typically go hand in hand. The complexities in dance, music, and their synchronisation make them fascinating to study from a computational creativity perspective. While several works have looked at generating dance for a given music, automatically generating music for a given dance remains under-explored. This capability could have several creative expression and entertainment applications. We present some early explorations in this direction. We present a search-based offline approach that generates music after processing the entire dance video and an online approach that uses a deep neural network to generate music on-the-fly as the video proceeds. We compare these approaches to a strong heuristic baseline via human studies and present our findings. We have integrated our online approach in a live demo! A video of the demo can be found here: https://sites.google.com/view/dance2music/live-demo.
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Cited by 1 Pith paper
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Dance to Music Generation leveraging Pre-training with Unpaired data and Contrastive Alignment
Beat-guided contrastive alignment of pretrained MotionBERT/MERT features plus ControlNet conditioning of AudioLDM improves dance–music alignment on AIST++ over a MusicGen textual-inversion baseline while remaining com...
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