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

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

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
In recent years,computing art has developed rapidly with the in-depth cross study of artificial intelligence generated con-tent(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 pro-spect.In this paper,we introduce innovative achievements in audio-visual content generation from the perspective of visual art genera-tion 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 op-portunities and challenges in the field of audio-visual synesthesia generation,and we provide a comprehensive discussion on them.

Artificial intelligence(AI)artaudio-visualartificial intelligence generated content(AIGC)multimodalartistic evalu-ation

Mengting Liu、Ying Zhou、Yuwei Wu、Feng Gao

展开 >

Advanced Institute of Information Technology,Peking University,Hangzhou 311215,China

School of Electronic and Computer Engineering,Shenzhen Graduate School,Peking University,Shenzhen 518000,China

Peng Cheng Laboratory,Shenzhen 518000,China

School of Arts,Peking University,Beijing 100871,China

展开 >

National Natural Science Foundation of ChinaNational Key Research and Development Program of China

621760062022YFF0902302

2024

10.1007/s11633-023-1453-5

机器智能研究(英文)
中国科学院自动化所

机器智能研究(英文)

CSTPCDEI
影响因子：0.49
ISSN：2731-538X
年,卷(期)：2024.21(1)
  • 1