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AI À̹ÌÁö »ý¼º±â ½ÃÀå ±Ô¸ð, Á¡À¯À², µ¿Ç⠺м® º¸°í¼ : ±¸¼º¿ä¼Òº°, ÃÖÁ¾»ç¿ëÀÚº°, Áö¿ªº°, ºÎ¹®º° ¿¹Ãø(2024-2030³â)AI Image Generator Market Size, Share & Trends Analysis Report By Component (Software, Services), By End-user (Media & Entertainment, Healthcare), By Region, And Segment Forecasts, 2024 - 2030 |
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The global AI image generator market size is anticipated to reach USD 1.08 billion by 2030, registering a CAGR of 17.7% from 2024 to 2030, according to a new report by Grand View Research, Inc. The increasing demand for visual content, advancements in AI technology, expanding use cases, integration with AR and VR, and ongoing research and development efforts, such as progressive growing GANs or style-based GANs, to generate higher-quality and more realistic images, position the AI image generator market for growth in the future.
Deep learning algorithms, particularly generative adversarial networks (GANs), have revolutionized the field of AI image generation. GANs enable the creation of highly realistic and high-quality images by pitting two neural networks against each other. As deep learning techniques continue to advance, the quality and realism of AI-generated images are improving, driving the market's growth. For instance, in August 2019, NVIDIA Corporation introduced StyleGAN as a significant advancement in GAN-based image generation. StyleGAN allows for generating highly realistic and diverse images by controlling different aspects of the image's style and content. It is widely used in various applications, including art, fashion, and entertainment. It enables users to create unique and visually appealing images by manipulating attributes such as facial features, clothing styles, and artistic styles.
AI image generators are integrated with AR and VR technologies to create immersive and realistic experiences. This integration allows for the real-time generation of high-quality visuals in virtual environments, contributing to the growth of the AI image generator market. For example, AI image generators can generate realistic virtual avatars or create virtual objects with detailed textures and appearances. The demand for AR and VR applications across industries, including gaming, training simulations, and virtual tours, will further drive the adoption of AI image generators. For instance, VR-based flight simulators have been widely adopted for pilot training. These simulations provide a realistic cockpit environment, allowing trainee pilots to practice flight maneuvers, emergency procedures, and instrument operations in a safe and controlled virtual environment.
The applications of AI image generators are expanding beyond traditional fields such as entertainment and gaming. Industries such as fashion, interior design, healthcare, and automotive are increasingly utilizing AI image generators to generate realistic product visuals, simulate design concepts, aid medical imaging, and enhance virtual experiences. Diversifying use cases will drive the demand for AI image generators and fuel market growth. For instance, AI image generators in healthcare can be developed to generate realistic medical images for training purposes or to simulate medical scenarios. Similarly, in architecture and interior design, AI image generators can generate photorealistic renderings of buildings and interior spaces. It is projected to witness the development of more domain-specific AI image generator technologies.