Call for Papers

HUARL seeks various types of papers (max 12 pages, including references), which include:

• Discussion Papers that delves into a specific topic or issue, presenting various perspectives and arguments.

• Survey Papers that capture the current state of research and present potential research gaps and future directions.

• Project Papers that give an overview of an ongoing/planning project by describing the approach and goals of the project.

• Research Papers that contribute state-of-the-art advances and provide results as evidence.

Researchers are invited to submit research papers and extended abstracts about technical artifacts at the intersection of AI, XR, and/or HCI. The workshop welcomes both technical papers, work-in-progress position papers, as well as demos in the areas, including, but not limited to: 

• Computer Vision in XR

  • Real-time object recognition and scene understanding

  • Gesture and Eye Recognition/Tracking

  • Multimodal Generative AI for Images

  • SLAM (Simultaneous Localization and Mapping) and Spatial Awareness

  • Deep Learning for user video and image analysis

• AI and Computer Graphics:

  • Neural rendering techniques for photorealistic and stylized visuals

  • 3D reconstruction methodologies using deep learning

  • AI-powered content adaptation for real-time rendering and animation

• Generative AI for XR Content

  • AI-driven 3D asset creation for immersive environments

  • Generative models for dynamic and personalized XR experiences

  • Text-to-3D or image-to-3D applications in XR content generation;

• Foundational AI Multimodal Models

  • AI models for bridging vision, language, and interaction in XR

  • AI for real-time semantic understanding in XR

  • XR systems as a data playground for training foundational AI models

• Applications of AI and XR Across Domains

  • XR for industrial training and task optimization

  • AI and XR in cultural heritage and digital preservation

  • AI and XR in education, training, and pedagogy

  • AI for media and entertainment in XR (e.g., immersive storytelling)

• AI and XR for Data Collection and Simulation

  • XR environments as a source for training AI models

  • Simulation-based testing of AI in virtual spaces

  • Leveraging XR for AI model evaluation and refinement

• Ethics of Human-Centric AI

  • Ethical implications of both AI and XR (e.g., bias and privacy concerns, emotional intelligence)

  • Transparent, trustworthy, and inclusive AI systems

These approaches could be applied across various domains, including but not limited to everyday activities, industry, cultural heritage, media, social sciences, history, and music.