3 accepted papers
Learning to retrieve dance poses from music, a cross-modal retrieval task, has gained prominence in assisting choreographers in creating dances that harmonize with music. The recent predominant approach is to map music into 3D pose and shape space, and then match it with dance poses [1]. However, we…
Choreography is an artful blend of technique and creativity, requiring the meticulous design of movement sequences in harmony with music. To support choreographers in this intricate task, this work proposes a "music-to-dance pose retrieval" system that uses music snippets to retrieve dance poses, pr…
We propose a generative model for music extension in this paper. The model is composed of two classifiers, one for music emotion and one for music tonality, and a generative adversarial network (GAN). Therefore, it can generate symbolic music not only based on low level spectral and temporal charact…