Cogeneration of Innovative Audio-visual Content: A New Challenge for Computing Art

In recent years, computing art has developed rapidly with the in-depth cross study of artificial intelligence generated content (AIGC) and the main features of artworks. Audio-visual content generation has gradually been applied to various practical tasks, including video or game score, assisting artists in creation, art education and other aspects, which demonstrates a broad application prospect. In this paper, we introduce innovative achievements in audio-visual content generation from the perspective of visual art generation and auditory art generation based on artificial intelligence (AI). We outline the development tendency of image and music datasets, visual and auditory content modelling, and related automatic generation systems. The objective and subjective evaluation of generated samples plays an important role in the measurement of algorithm performance. We provide a cogeneration mechanism of audio-visual content in multimodal tasks from image to music and display the construction of specific stylized datasets. There are still many new opportunities and challenges in the field of audio-visual synesthesia generation, and we provide a comprehensive discussion on them.