Research on the Integration and Practice of Innovative Intelligent Technologies in Oil Painting Art Creation

Currently, domestic oil painting creation in China faces challenges such as the interruption of traditional technique inheritance, the imbalance between creative efficiency and artistic texture, and difficulties in adapting to new materials. This study integrates literature research, technical testing, and empirical analysis to systematically organize the application logic of intelligent technologies—including artificial intelligence (AI), virtual reality (VR), and big data—in oil painting creation. Specifically, it constructs a three-level integration framework of "algorithm foundation - tool layer - application scenario," incorporating test parameters of technologies such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). By analyzing practical cases of 50 domestic young oil painters and 200 of their works, the study identifies three human-machine collaboration models: auxiliary collaboration, interactive collaboration, and generative collaboration. To address pain points like brushstroke distortion and ambiguous copyright definition, it proposes a solution framework of "technical optimization - ethical regulation - ecosystem construction."The research shows that through the mechanism of "data-driven - manual calibration - full-process integration," intelligent technologies can increase creative efficiency by more than 300% while preserving the emotional warmth and cultural attributes of oil painting art. This provides a practical path for the innovative inheritance of domestic oil painting art in China.