论文标题
ganterpretations
GANterpretations
论文作者
论文摘要
自从引入生成对抗网络（GANS）[Goodfellow等，2014]以来，这些生成模型的技术进步定期（例如，Arjovsky等人[2017]）和创造性使用（例如，[例如[Karras等人，2019年，2019年，Zhu等，Zhu等，2017，2017，Jin，2017]）。在这项工作中，我们提出了一种使用gan的力量来自动生成视频来伴随录音的方法，通过对齐录音的频谱属性。这使音乐家能够探索多模式创意表达的新形式，音乐表演可以引起AI生成的音乐视频，并以所述表演为指导，以及一种创建视觉叙事以跟随故事情节的媒介（类似于Frosst和Kereliuk [2019]）。
Since the introduction of Generative Adversarial Networks (GANs) [Goodfellow et al., 2014] there has been a regular stream of both technical advances (e.g., Arjovsky et al. [2017]) and creative uses of these generative models (e.g., [Karras et al., 2019, Zhu et al., 2017, Jin et al., 2017]). In this work we propose an approach for using the power of GANs to automatically generate videos to accompany audio recordings by aligning to spectral properties of the recording. This allows musicians to explore new forms of multi-modal creative expression, where musical performance can induce an AI-generated musical video that is guided by said performance, as well as a medium for creating a visual narrative to follow a storyline (similar to what was proposed by Frosst and Kereliuk [2019]).
