AI Art
AI art uses machine learning, particularly diffusion models and generative adversarial networks (GANs), to create images from text prompts or other inputs like sound. Current research focuses on improving image quality, addressing issues like stylistic homogeneity and copyright concerns, and exploring the integration of AI art into various creative fields such as fashion design and architecture. This rapidly evolving field is prompting discussions about the nature of creativity, the ethical implications of AI-generated art, and its potential impact on artistic practices and the broader creative economy.
Papers
Robot Synesthesia: A Sound and Emotion Guided AI Painter
Vihaan Misra, Peter Schaldenbrand, Jean Oh
Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples
Chumeng Liang, Xiaoyu Wu, Yang Hua, Jiaru Zhang, Yiming Xue, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan