Intersecting Realms: Examining the Convergence of Vision and AI in Extended Reality Graphics

Exploring the integration of Artificial Intelligence (AI) with Extended Reality (XR), this research addresses four critical questions: (R.Q.1) How can AI enhance the realism of virtual environments through dynamic texture and material generation? (R.Q.2) What methods can be developed for AI-driven adaptive learning systems that adjust environment difficulty and content based on user performance? (R.Q.3) What are the best practices for training AI to achieve real-time object recognition, spatial mapping, and scene understanding in diverse environments? And (R.Q.4) How have the themes and focal areas within XR research evolved over time, and what are the predominant topics and trends as evidenced by bibliographic references and citations in scholarly reviews? A thorough literature review and systematic analysis confirm that AI significantly advances the fidelity and interactivity of XR environments. This research not only highlights how AI enriches user experience and procedural functioning in XR but also delves into the evolutionary trajectories in XR research, identifying major thematic trends and shifts over time. These findings underscore the complex interplay between technological advancements and thematic trends within the academic discourse on XR, advocating for consistent innovation and ethical considerations in the utilization of AI across various domains, including education, healthcare, and entertainment.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3599337
Primary Topic
Prenatal Screening and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
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article

Intersecting Realms: Examining the Convergence of Vision and AI in Extended Reality Graphics

IEEE Access
Prenatal Screening and Diagnostics
article

Intersecting Realms: Examining the Convergence of Vision and AI in Extended Reality Graphics

article en

Abstract

Exploring the integration of Artificial Intelligence (AI) with Extended Reality (XR), this research addresses four critical questions: (R.Q.1) How can AI enhance the realism of virtual environments through dynamic texture and material generation? (R.Q.2) What methods can be developed for AI-driven adaptive learning systems that adjust environment difficulty and content based on user performance? (R.Q.3) What are the best practices for training AI to achieve real-time object recognition, spatial mapping, and scene understanding in diverse environments? And (R.Q.4) How have the themes and focal areas within XR research evolved over time, and what are the predominant topics and trends as evidenced by bibliographic references and citations in scholarly reviews? A thorough literature review and systematic analysis confirm that AI significantly advances the fidelity and interactivity of XR environments. This research not only highlights how AI enriches user experience and procedural functioning in XR but also delves into the evolutionary trajectories in XR research, identifying major thematic trends and shifts over time. These findings underscore the complex interplay between technological advancements and thematic trends within the academic discourse on XR, advocating for consistent innovation and ethical considerations in the utilization of AI across various domains, including education, healthcare, and entertainment.

IEEE AccessVol. 13
University of Tabuk (SA)
Industry, innovation and infrastructure
Openalex Percentile: Top 34%
Prenatal Screening and Diagnostics
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Intersecting Realms: Examining the Convergence of Vision and AI in Extended Reality Graphics · IEEE Access (2025) | TGRS Research Map | TGRS