The integration of artificial intelligence (AI) with immersive technologies represents one of the most promising frontiers in contemporary research. The increased computing power of modern GPUs has improved the quality and polygonal density of 3D scenes. Real-time computing that can be performed by modern processors and immersive technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR) can benefit from creating synthetic virtual environments of more and more interactive and personalized. Experts can use AI to accelerate the development of 3D models or textures by enabling rapid prototyping of environments and scenarios. In therapeutic settings, AI-based VR applications can help people who have difficulty accessing medical sites and following therapeutic programs remotely. Additionally, neural networks, especially convolutional neural networks (CNN), can benefit from AI-generated synthetic photorealistic data for problems and application areas where creating datasets based solely on real photographs is particularly complex.
The development of these innovative applications also requires a study of innovative user interfaces to improve user interaction and immersive experience. One of the main problems with immersive reality software (VR, AR and MR) is input devices, which do not allow complete control. We are limited by joysticks, mice, keyboards and other similar devices. Innovative input systems and new user interfaces that can provide users with greater expressiveness and interaction capabilities in virtual scenarios should be investigated.
Additionally, this research topic explores how AI – particularly modern generative models based on large language models (LLMs) – can be leveraged to develop more effective immersive applications that address complex problems (particularly in the education, synthetic content creation and telerehabilitation). Recent technological advancements have made these technologies more mature, with reduced costs and latency, making them increasingly accessible for broader applications. The collection will focus on how these AI models can facilitate the creation of complex immersive environments. For example, creating textures for 3D meshes, traditionally done manually using software like Blender or photogrammetry, is time-consuming. However, taking advantage of modern LLMs can speed up this process while maintaining comparable quality. A key topic we want to address is rapid prototyping of 3D environments using AI, ensuring the end result remains high quality. Additionally, AI training can be accelerated by generating synthetic data in computer graphics environments. These synthetic environments allow the creation of random combinations of shadow, light, and object positions, enabling the development of valuable datasets in contexts where collecting real data is difficult or dangerous. By addressing these challenges, we aim to unlock new possibilities for immersive environments that fully exploit the potential of AI.
Topics of interest include, but are not limited to:
– Improve the effectiveness of therapy and rehabilitation with AI-based VR solutions
– Study and analyze the impact of AI technologies on cognitive and emotional engagement in immersive learning platforms
– Integration of AI models to create immersive multi-sensory VR experiences by modulating tactile, visual and auditory outputs
– Analyze how generative AI models can generate synthetic data in VR to accelerate the object recognition pipeline
– Study the use of AI models to populate three-dimensional environments with content (meshes, textures, sounds, texts)
– Analyze from the point of view of human-machine interaction how to implement these technologies
– Design dynamic interfaces that adapt based on user behavior and their expertise in using the application, or that adapt based on their moods and emotions
– Develop new methods of interaction with virtual scenarios that allow users greater expressiveness, control and immersion, also with the help of AI
Keywords: artificial intelligence (AI), large language models (LLM), GPT, virtual reality (VR), mixed reality (MR), augmented reality (AR), generation of synthetic datasets
Important note: All contributions to this research topic must fall within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more appropriate section or journal at any stage of peer review.
The integration of artificial intelligence (AI) with immersive technologies represents one of the most promising frontiers in contemporary research. The increased computing power of modern GPUs has improved the quality and polygonal density of 3D scenes. Real-time computing that can be performed by modern processors and immersive technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR) can benefit from creating synthetic virtual environments of more and more interactive and personalized. Experts can use AI to accelerate the development of 3D models or textures by enabling rapid prototyping of environments and scenarios. In therapeutic settings, AI-based VR applications can help people who have difficulty accessing medical sites and following therapeutic programs remotely. Additionally, neural networks, especially convolutional neural networks (CNN), can benefit from AI-generated synthetic photorealistic data for problems and application areas where creating datasets based solely on real photographs is particularly complex.
The development of these innovative applications also requires a study of innovative user interfaces to improve user interaction and immersive experience. One of the main problems with immersive reality software (VR, AR and MR) is input devices, which do not allow complete control. We are limited by joysticks, mice, keyboards and other similar devices. Innovative input systems and new user interfaces that can provide users with greater expressiveness and interaction capabilities in virtual scenarios should be investigated.
Additionally, this research topic explores how AI – particularly modern generative models based on large language models (LLMs) – can be leveraged to develop more effective immersive applications that address complex problems (particularly in the education, synthetic content creation and telerehabilitation). Recent technological advancements have made these technologies more mature, with reduced costs and latency, making them increasingly accessible for broader applications. The collection will focus on how these AI models can facilitate the creation of complex immersive environments. For example, creating textures for 3D meshes, traditionally done manually using software like Blender or photogrammetry, is time consuming. However, taking advantage of modern LLMs can speed up this process while maintaining comparable quality. A key topic we want to address is rapid prototyping of 3D environments using AI, ensuring the end result remains high quality. Additionally, AI training can be accelerated by generating synthetic data in computer graphics environments. These synthetic environments allow the creation of random combinations of shadow, light, and object positions, enabling the development of valuable datasets in contexts where collecting real data is difficult or dangerous. By addressing these challenges, we aim to unlock new possibilities for immersive environments that fully exploit the potential of AI.
Topics of interest include, but are not limited to:
– Improve the effectiveness of therapy and rehabilitation with AI-based VR solutions
– Study and analyze the impact of AI technologies on cognitive and emotional engagement in immersive learning platforms
– Integration of AI models to create immersive multi-sensory VR experiences by modulating tactile, visual and auditory outputs
– Analyze how generative AI models can generate synthetic data in VR to accelerate the object recognition pipeline
– Study the use of AI models to populate three-dimensional environments with content (meshes, textures, sounds, texts)
– Analyze from the point of view of human-machine interaction how to implement these technologies
– Design dynamic interfaces that adapt based on user behavior and their expertise in using the application, or that adapt based on their moods and emotions
– Develop new methods of interaction with virtual scenarios that allow users greater expressiveness, control and immersion, also with the help of AI
Keywords: artificial intelligence (AI), large language models (LLM), GPT, virtual reality (VR), mixed reality (MR), augmented reality (AR), generation of synthetic datasets
Important note: All contributions to this research topic must fall within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more appropriate section or journal at any stage of peer review.
