AuraLuxMuse is a system that automates aesthetic stage lighting design by integrating expert knowledge, representation learning, and preference-adaptive modeling. It encodes music and professional cue sequences into a shared retrieval space, estimates cue-event density, and retargets fixture commands to the stage, providing editable cues for designers. The system features Lighting‑Aligned Music Pretraining (LAMP) for audio‑lighting alignment and Preference‑Adaptive Mixture of Experts (PAMoE) for designer‑intent‑driven cue adaptation, and is evaluated using the new Musilux dataset and both virtual and professional labs.
By Junyu Deng, Jiale Cao, Mengtian Li, Zhongxia Ji, Ruhua Chen, Yiyi He, Guangnan Ye, Zuo Hu
arXiv:2606. 30642v1 Announce Type: cross Abstract: Full-length song generation must preserve coherence and musicality, render detailed vocal and accompaniment acoustics, and follow lyrics and prompts.
By Shun Lei, Huaicheng Zhang, Dapeng Wu, Yaoxun Xu, Lishi Zuo, Wei Tan, Hangting Chen, Guangzheng Li, Jianwei Yu, Zhiyong Wu, Dong Yu
arXiv:2608. 06751v1 Announce Type: cross Abstract: Artist-grounded image generation requires more than appending an artist name to a prompt.
By Kuan Xing, Ye Wang, Changyi Gan, Yuheng Li, Thao Nguyen, Yi Chang, Yilin Wang
arXiv:2502. 00023v2 Announce Type: replace-cross Abstract: Our research explores the development and application of musical agents, human-in-the-loop generative AI systems designed to support music performance and improvisation within co-creative spaces.
By Keon Ju M. Lee, Philippe Pasquier
Music-driven dance video generation aims to synthesize expressive human motion that is temporally aligned with music while maintaining high visual fidelity. Despite recent progress, existing methods still face two key limitations: the lack of large-scale, high-quality dance video datasets, and the absence of principled frameworks for integrating music as a complementary conditioning signal into Video Generation Foundation Models.
arXiv:2606. 00629v1 Announce Type: cross Abstract: Sound design workflows frequently oscillate between time-consuming library searches and the complexity of procedural synthesis, with practitioners typically relying on disconnected tools to address each challenge separately.
By Nelly Garcia, Aditya Bhattacharjee, Gabryel Mason-Williams, Israel Mason-Williams, Emmanouil Benetos, Joshua Reiss