中国计算机学会(CCF)推荐学术会议-B(计算机图形学与多媒体):EuroVis 2026

EuroVis 2026

After more than a decade, the annual Eurovis Conference, organized by the Visualization, Text Analytics, and Graphics (VisTAG) Group at the University of Nottingham, returns to the islands of the UK, 8-12 June 2026.  Eurovis 2026 is the 29th annual visualization and visual analytics event organized by the Eurographics Working group on Data Visualization.

Eurovis has been an international Eurographics visualization event held in Europe annually since 1990. It began as the Eurographics Workshop on Visualization in Scientific Computing (ViSC) and became the joint Eurographics/IEEE Visualization Symposium (VisSym) in 1999.  It was renamed to EuroVis in 2005 and became a Eurographics Conference in 2012. Since 2008 its proceedings are published as a special issue of Computer Graphics Forum (EG/WIley CGF).

重要信息

CCF推荐:B(计算机图形学与多媒体)

录用率:25%(2020年)

时间地点:2026年6月8日-诺宁汉·英国

截稿时间:2025年11月26日

Full Papers

We encourage submissions from all areas of visualization and visual analytics.

Techniques: novel algorithms, visual encoding methods, and/or interaction techniques for data analysis, exploration, or communication. All sub-areas of visualization and visual analytics are welcomed, including high-dimensional, time-series, spatial, geographic, text, hierarchical, and network data. Techniques may be specialized for specific devices or form-factors (e.g., mobile or wall-scale visualization).

Systems: new software frameworks, languages, or tools for visualization; systems for large-scale visualization; integrated graphical systems for visual analysis or interactive machine learning; collaborative and web-scale visualization systems.

Applications & Design Studies: novel use of visualization to address problems in an application domain, including accounts of innovative system design, deployment and impact. We welcome diverse application areas, including the physical sciences, life sciences, social sciences, engineering, arts, sports, and humanities.

Evaluation & Empirical Research: Comparative evaluation of competing visualization approaches; controlled experiments to inform visualization best practices; longitudinal and qualitative studies to understand user needs, visualization adoption, and use.

Theory: models of visual encoding, interaction, and/or analysis tasks; implications from theories of perception, cognition, design, and/or aesthetics; methods for automated design or visualization recommendation.

Author Guidlines for Full Papers

The maximum length for submitted papers to the full papers track is 10 pages (in Computer Graphics Forum (CGF) style, including all images and acknowledgements, but excluding references).

References should not exceed 2 pages. Authors are encouraged to use supplementary documents to provide extra content. Papers exceeding the maximum allowed number of pages will be automatically rejected.

Authors have the option to submit their papers anonymously. In contrast to previous years, double-blind reviewing is optional, not required: authors may choose to disclose their identities to the reviewers. The reviewing process does not consider anonymity as a factor. The process will attempt to preserve anonymity of authors of anonymized submissions. However, the program committee, which is responsible for half of the reviews, will know the authors of submissions reviewed by them. This is required for selecting reviewers without conflict of interests. Please take note that submissions may be checked for plagiarism.

(SCI三维路径规划对比)25年最新五种智能算法优化解决无人机路径巡检三维路径规划对比(灰雁算法真菌算法吕佩尔狐阳光生长研究(Matlab代码实现)内容概要:本文档主要介绍了一项关于无人机三维路径巡检规划的研究,通过对比2025年最新的五种智能优化算法(包括灰雁算法、真菌算法、吕佩尔狐算法、阳光生长算法等),在复杂三维环境中优化无人机巡检路径的技术方案。所有算法均通过Matlab代码实现,并重点围绕路径安全性、效率、能耗和避障能力进行性能对比分析,旨在为无人机在实际巡检任务中的路径规划提供科学依据和技术支持。文档还展示了多个相关科研方向的案例代码资源,涵盖路径规划、智能优化、无人机控制等多个领域。; 适合人群:具备一定Matlab编程基础,从事无人机路径规划、智能优化算法研究或自动化、控制工程方向的研究生、科研人员及工程技术人员。; 使用场景及目标:① 对比分析新型智能算法在三维复杂环境下无人机路径规划的表现差异;② 为科研项目提供可复现的算法代码实验基准;③ 支持无人机巡检、灾害监测、电力线路巡查等实际应用场景的路径优化需求; 阅读建议:建议结合文档提供的Matlab代码进行仿真实验,重点关注不同算法在收敛速度、路径长度和避障性能方面的表现差异,同时参考文中列举的其他研究案例拓展思路,提升科研创新能力。
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