Computer Graphics Forum is the premier journal for in-depth technical articles on computer graphics. Published jointly by Wiley and Eurographics, we enable our readers to keep pace with this fast-moving field with our rapid publication times and coverage of major international computer graphics events, including the annual Eurographics Conference proceedings. We welcome original research papers on a wide range of topics including image synthesis, rendering, perception and visualisation.

Articles

Original Article
Open access

ConAn: Measuring and Evaluating User Confidence in Visual Data Analysis Under Uncertainty

M. Musleh, D. Ceneda, H. Ehlers, R. G. Raidou, 
  •  29 November 2024

Graphical Abstract

ConAn: Measuring and Evaluating User Confidence in Visual Data Analysis Under Uncertainty Issue ,

We propose a quantitative approach to measure user confidence by introducing a set of network metrics to analyse a provenance graph of user interaction. Our results indicate that our proposed metrics and the provenance network representation support a better evaluation of user confidence and effective development of guidance in VA.

ORIGINAL ARTICLE
Open access

Mesh Simplification for Unfolding*

M. Bhargava, C. Schreck, M. Freire, P. A. Hugron, S. Lefebvre, S. Sellán, B. Bickel, 
  •  15 November 2024

Graphical Abstract

Mesh Simplification for Unfolding* Issue ,

A computational approach for unfolding 3D shapes isometrically into the plane as a single patch without overlapping triangles. The input shape is modified by locally displacing vertices and collapsing edges, guided by the unfolding process till it admits an overlap-free unfolding.

ORIGINAL ARTICLE

Conditional Font Generation With Content Pre‐Train and Style Filter

Yang Hong, Yinfei Li, Xiaojun Qiao, Junsong Zhang, 
  •  15 November 2024

Graphical Abstract

Conditional Font Generation With Content Pre-Train and Style Filter Issue ,

We propose a conditional generation method that incorporates pre-trained content representations for high-fidelity Chinese character font generation, and our style filter achieves efficient extraction of stylistic features from arbitrary combinations of references.

Image Synthesis

DiffPop: Plausibility‐Guided Object Placement Diffusion for Image Composition

Jiacheng Liu, Hang Zhou, Shida Wei, Rui Ma, 
  •  14 November 2024
3D Modeling and Editing I

iShapEditing: Intelligent Shape Editing with Diffusion Models

Jing Li, Juyong Zhang, Falai Chen, 
  •  8 November 2024
More articles

The following is a list of the most cited articles based on citations published in the last three years, according to CrossRef.

Efficient RANSAC for Point‐Cloud Shape Detection

R. Schnabel, R. Wahl, R. Klein, 
  •  214-226
  •  21 May 2007

Crowds by Example

Alon Lerner, Yiorgos Chrysanthou, Dani Lischinski, 
  •  655-664
  •  12 October 2007

Super 4PCS Fast Global Pointcloud Registration via Smart Indexing

Nicolas Mellado, Dror Aiger, Niloy J. Mitra, 
  •  205-215
  •  23 August 2014

State of the Art on Neural Rendering

A. Tewari, O. Fried, J. Thies, V. Sitzmann, S. Lombardi, K. Sunkavalli, R. Martin-Brualla, T. Simon, J. Saragih, M. Nießner, R. Pandey, S. Fanello, G. Wetzstein, J.-Y. Zhu, C. Theobalt, M. Agrawala, E. Shechtman, D. B Goldman, M. Zollhöfer, 
  •  701-727
  •  13 July 2020

A Concise and Provably Informative Multi‐Scale Signature Based on Heat Diffusion

Jian Sun, Maks Ovsjanikov, Leonidas Guibas, 
  •  1383-1392
  •  31 August 2009
More articles

The most read articles published in the Last 5 Years

Open access

State of the Art of Visual Analytics for eXplainable Deep Learning

B. La Rosa, G. Blasilli, R. Bourqui, D. Auber, G. Santucci, R. Capobianco, E. Bertini, R. Giot, M. Angelini, 

Graphical Abstract

State of the Art of Visual Analytics for eXplainable Deep Learning Issue 1, 2023

This survey systematically reports the contributions of Visual Analytics for eXplainable Deep Learning, spots gaps, serves as an anthology of visual analytical solutions ready to be exploited by the Deep Learning community, proves the degree of maturity, ease of integration, results for specific domains and finally identifies future research challenges.

Effective Use of Likert Scales in Visualization Evaluations: A Systematic Review

Laura South, David Saffo, Olga Vitek, Cody Dunne, Michelle A. Borkin, 
Open access

A survey of Optimal Transport for Computer Graphics and Computer Vision

Nicolas Bonneel, Julie Digne, 
Open access

State of the Art in Dense Monocular Non‐Rigid 3D Reconstruction

Edith Tretschk, Navami Kairanda, Mallikarjun B R, Rishabh Dabral, Adam Kortylewski, Bernhard Egger, Marc Habermann, Pascal Fua, Christian Theobalt, Vladislav Golyanik, 
Open access

Recent Trends in 3D Reconstruction of General Non‐Rigid Scenes

Raza Yunus, Jan Eric Lenssen, Michael Niemeyer, Yiyi Liao, Christian Rupprecht, Christian Theobalt, Gerard Pons-Moll, Jia-Bin Huang, Vladislav Golyanik, Eddy Ilg, 

Neural Fields in Visual Computing and Beyond

Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent sitzmann, Srinath Sridhar, 
Open access

The State of the Art of Spatial Interfaces for 3D Visualization

Lonni Besançon, Anders Ynnerman, Daniel F. Keefe, Lingyun Yu, Tobias Isenberg, 

Graphical Abstract

The State of the Art of Spatial Interfaces for 3D Visualization Issue 1, 2021

We survey the state of the art of spatial interfaces for 3D visualization. Interaction techniques are crucial to data visualization processes and the visualization research community has been calling for more research on interaction for years. Yet, research papers focusing on interaction techniques, in particular for 3D visualization purposes, are not always published in visualization venues, sometimes making it challenging to synthesize the latest interaction and visualization results.

Open access

A Survey of Indicators for Mesh Quality Assessment

T. Sorgente, S. Biasotti, G. Manzini, M. Spagnuolo, 
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