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IEEE Computer Graphics and Applications

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インパクトファクター:
1.4
出版社:
IEEE
ISSN:
0272-1716
閲覧:
33320
フォロー:
15

論文募集

IEEE Computer Graphics and Applications is an academic journal published by IEEE. (ISSN 0272-1716, impact factor 1.4).

About IEEE Computer Graphics & Applications Distinct from other IEEE publications, CG&A emphasizes the applied and experiential dimensions of graphical technologies. It serves as an essential resource for professionals and researchers working at the forefront of computer graphics and its wide-ranging applications across STEM fields, the arts, education, business, and beyond. Scope IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics by publishing work that spans foundational research to practical implementation. The magazine focuses on computer graphics, visualization, virtual reality, and interactive techniques. These topics often intersect, creating a multidisciplinary domain for exploring new technologies.
最終更新：Dou Sun（）

Special Issues

Special Issue on AI Governance, Authenticity, and Provenance for Visual Media 投稿締切日: 2026-09-30 The rapid evolution of deep learning, particularly generative models for images and videos, is transforming how visual media is created, edited, and distributed. At the same time, it raises urgent concerns about authenticity, provenance, and accountability. Synthetic media can be produced at scale, editing histories may be obscured, and verification is increasingly difficult for both humans and automated systems. Preserving trust in visual media therefore requires technical infrastructures that record, verify, and communicate how content was created and transformed. This special issue invites submissions that treat AI governance, authenticity, and provenance as visual computing problems, with technical contributions in computer graphics, visualization, and visual analytics. We also welcome work from HCI, AI/ML, multimedia systems, and security when the core contribution centers on visual media. We particularly encourage submissions from the visual analytics community on interactive systems for exploring and communicating provenance and authenticity in visual media workflows. Visual media includes photographs, videos, generative imagery, rendered content, AR/VR/XR assets, 3D models, and scientific visualizations produced through complex toolchains. Submissions may address algorithmic approaches (e.g., watermarking, signatures, perceptual cues, and visual forensics), system pipelines for provenance tracking and verification, or visualization and interaction techniques supporting human inspection and sensemaking. Strong submissions should include a substantial contribution in visual media, visualization, interaction, or system contribution and demonstrate relevance to real-world workflows such as journalism, publishing, media distribution, scientific visualization, legal and archival contexts, GLAM institutions, and creative production pipelines. In this context, AI governance refers to visual computing systems that support transparency and accountability in visual media production and distribution, including provenance-aware pipelines, audit trails, disclosure and labeling interfaces, and emerging standards (e.g., C2PA, CAWG, IPTC, JPEG Trust, TDMRep). Papers must make a clear contribution to graphics or visualization systems and not simply summarize standards or advocate positions without a technical contribution. Topics of interest include, but not limited to: Visual and multimodal fact-checking tools for images and videos Robust watermarking, fingerprinting, and authenticity signals for visual media Digital forensics and artifact analysis for images and videos Interactive provenance visualization for content history understanding and communication Visualization for compliance, auditing, and accountability Visual cues and indicators for signaling authenticity Human-in-the-loop sensemaking interfaces for content authenticity assessment Adversarial robustness of authenticity methods Provenance establishment and tracking methods for visual media workflows Interfaces supporting disclosure, consent, and content labeling Platform-level governance and moderation tools for visual media integrity In addition to research papers, IEEE CG&A invites Perspective and Overview Paper (POP) submissions related to this theme. POP papers may include surveys, tutorials, state-of-the-art reports, or forward-looking perspectives that synthesize knowledge or explore emerging aspects of the CFP theme. For details, visit  CG&A Author Information Page, but please submit your paper to this special issue rather than the regular POP queue. https://www.computer.org/digital-library/magazines/cg/cfp-ai-governance-authenticity-provenance
最終更新：Dou Sun（）

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