Computer Graphics & Visual Computing (CGVC) 2025

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https://diglib.eg.org/handle/10.2312/3607216

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Browsing Computer Graphics & Visual Computing (CGVC) 2025 by Subject "Applied computing → Computer games"

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    Efficient GPU-Based Real-Time Rendering of Curved Geometry for Large-Scale Applications
    (The Eurographics Association, 2025) Qaiser, Sharjeel R.; Sheng, Yun; Slingsby, Aidan
    This paper presents an efficient and practical approach to GPU-based real-time generation, simulation and rendering of approximated curved geometry. We focus on how this approach can be embedded into a resource-intensive application, such as a large-scale real-time strategy game, which requires a significantly large number of instances of these temporally persistent primitives, which we call ribbons. A key step in our technique is minimizing data transfer between the CPU and GPU, resulting in our usage of transient resources and employment of parallel data recycling methods, which map well to a SIMD architecture. Furthermore, we detail optimizations such as batching ribbon instances by material for rendering, grouping segments together for geometry construction and early culling of control points.
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    Run-time Performance Comparison of Sparse-set and Archetype Entity-Component Systems
    (The Eurographics Association, 2025) Cox, Louis; Williams, Benjamin; Vickers, James; Ward, Davin; Headleand, Christopher; Sheng, Yun; Slingsby, Aidan
    Entity-Component System (ECS) architectures have emerged as a powerful alternative to traditional object-oriented solutions in video games and real-time simulations. However, different ECS implementations present distinct trade-offs between iteration speed and modification costs. Despite its growing adoption, a comparative analysis on the performance characteristics of ECS implementation types has yet to be conducted. This study compares the performance of two widely-used ECS implementations: sparse-set and archetype-based. To facilitate this, an implementation of each architecture was developed in C++20 and their performance was examined in terms of iteration speed and entity modification costs. The results show sparse-set ECSes enable cheaper entity modifications but scale poorly during iteration, while archetypes excel at large-scale iteration through cache efficiency but incur higher composition change costs. These findings provide valuable and actionable guidance for developers selecting ECS architectures for their specific applications.
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    Social Dimensions in Content Creation for Games: A Systematic Review of Fairness, Social Bias, and Diversity in Computational Character and Environment Generation
    (The Eurographics Association, 2025) Horst, Robin; Dörner, Ralf; Sheng, Yun; Slingsby, Aidan
    Computational content generation increasingly shapes digital games, visual computing, and interactive environments, automating the creation of characters and environments. However, these systems also raise complex challenges related to fairness, social bias, and representational diversity. We present a systematic literature review of 37 recent studies addressing fairness-aware computational content generation across character creation, face modeling, and procedural environments. We analyze both algorithmic strategies - including deep learning, reinforcement learning, generative adversarial networks, and optimization - as well as design-oriented frameworks such as behavioral, participatory, and cultural methods. Our review reveals substantial conceptual fragmentation in how fairness, social bias, and diversity are defined, measured, and operationalized across domains. While several metrics (e.g., statistical parity, balanced accuracy, generative diversity scores) are applied, standardized computational frameworks and large-scale auditing tools remain largely absent. We conclude by outlining key research challenges, including metric standardization, scalable fairness, social bias, and diversity auditing, cross-cultural dataset development, and interdisciplinary collaboration, to advance aware content generation in games.