Journal: IEEE Computer Graphics and Applications

Abbreviation

IEEE Comput. Graph. Appl.

Publisher

IEEE

Journal Volumes

ISSN

0272-1716
1558-1756

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Publications 1 - 10 of 16
  • Getting to the Point...?
    Item type: Journal Article
    Gross, Markus (2006)
    IEEE Computer Graphics and Applications
  • 3D recording for archaeological fieldwork
    Item type: Journal Article
    Pollefeys, Marc; Van Gool, Luc; Vergauwen, Maarten; et al. (2003)
    IEEE Computer Graphics and Applications
  • VR-Based Simulators for Training in Minimally Invasive Surgery
    Item type: Journal Article
    Basdogan, Cagatay; Sedef, Mert; Harders, Matthias; et al. (2007)
    IEEE Computer Graphics and Applications
  • Point-based computer graphics
    Item type: Other Journal Item
    Pfister, Hanspeter; Gross, Markus (2004)
    IEEE Computer Graphics and Applications
  • Building intelligent environments with smart-its
    Item type: Journal Article
    Holmquist, L.E.; Gellersen, H.W.; Kortuem, G.; et al. (2004)
    IEEE Computer Graphics and Applications
  • Demystifying Quadrilateral Remeshing
    Item type: Journal Article
    Panozzo, Daniele (2015)
    IEEE Computer Graphics and Applications
  • Which Biases and Reasoning Pitfalls Do Explanations Trigger Decomposing Communication Processes in Human-AI Interaction
    Item type: Journal Article
    El-Assady, Mennatallah; Moruzzi, Caterina (2022)
    IEEE Computer Graphics and Applications
    Collaborative human-AI problem-solving and decision making rely on effective communications between both agents. Such communication processes comprise explanations and interactions between a sender and a receiver. Investigating these dynamics is crucial to avoid miscommunication problems. Hence, in this article, we propose a communication dynamics model, examining the impact of the sender's explanation intention and strategy on the receiver's perception of explanation effects. We further present potential biases and reasoning pitfalls with the aim of contributing to the design of hybrid intelligence systems. Finally, we propose six desiderata for human-centered explainable AI and discuss future research opportunities.
  • Modeling Virtual Humans
    Item type: Other Journal Item
    Bender, Jan; Erleben, Kenny; Solenthaler, Barbara (2017)
    IEEE Computer Graphics and Applications
  • News Globe: Visualization of Geolocalized News Articles
    Item type: Journal Article
    Ingulfsen, Nicholas; Schaub-Meyer, Simone; Gross, Markus; et al. (2022)
    IEEE Computer Graphics and Applications
    The number of online news articles available nowadays is rapidly increasing. When exploring articles on online news portals, navigation is mostly limited to the most recent ones. The spatial context and the history of topics are not immediately accessible. To support readers in the exploration or research of articles in large datasets, we developed an interactive 3D globe visualization. We worked with datasets from multiple online news portals containing up to 45,000 articles. Using agglomerative hierarchical clustering, we represent the referenced locations of news articles on a globe with different levels of detail. We employ two interaction schemes for navigating the viewpoint on the visualization, including support for hand-held devices and desktop PCs, and provide search functionality and interactive filtering. Based on this framework, we explore additional modules for jointly exploring the spatial and temporal domain of the dataset and incorporating live news into the visualization.
  • Generative AI for Computer Graphics
    Item type: Other Journal Item
    Sharma, Rajesh; Azevedo, Vinicius C.; Bednarz, Tomasz; et al. (2025)
    IEEE Computer Graphics and Applications
    Generative AI has emerged as a transformative force in the realm of computer graphics, offering innovative methods that push the boundaries of creativity, efficiency, and realism. In this special issue, we delve into the myriad ways in which generative AI is reshaping the field, with six articles that explore its applications across a wide range of topics. These contributions cover advancements in neural networks for image generation, AI-assisted design tools, deep learning techniques for realistic simulations, and the future of AI-driven animation. By examining both the theoretical and practical implications of these developments, this issue provides a comprehensive overview of how generative AI is enhancing the art and science of computer graphics. As the field continues to evolve, the articles in this issue offer a glimpse into the exciting possibilities that lie ahead, illuminating the potential of AI to redefine creative workflows and technical innovations in graphics.
Publications 1 - 10 of 16