Graphical Models (GMOD) is internationally recognized as a highly rated, top-tier journal and is focused on the creation, geometric processing, animation, and visualization of graphical and geometric models and on their applications in engineering, science, culture, and entertainment. GMOD provides its readers with thoroughly reviewed and carefully selected papers that disseminate exciting innovations, that teach rigorous theoretical foundations, that propose robust and efficient solutions, or that describe ambitious systems or applications in a variety of topics.
We invite papers in five categories: 1) research (contributions of novel theoretical or practical approaches or solutions), 2) survey (opinionated views of the state-of-the-art and challenges in a specific topic), 3) system (the architecture and implementation details of innovative architecture for a complete system that supports model/animation design, acquisition, analysis, visualization), 4) application (description of a novel application of know techniques and evaluation of its impact), or 5) lecture (an elegant and inspiring perspective on previously published results that clarifies them and teaches them in a new way).
GMOD offers its authors an accelerated review, feedback from experts in the field, immediate online publication of accepted papers, no restriction on color and length (when justified by the content), and broad promotion of published papers. A prestigious group of editors selected from among the premier international researchers in their fields oversees the review process.
Because the timely publication of research results is important for the careers of our authors and for the vitality of the field, GMOD is putting in place its R3 (Rapid Response Review) system, which strives to provide authors with a preliminary decision within an average of one month after submission.
The following are examples of topics typically covered in GMOD:
Shape processing: Shape analysis and understanding. Bounding volumes and geometric proxies. Correspondence, registration, matching, and retrieval. Detection of ridges, features, patterns, and symmetries. Measures of volume, compactness, or convexity. Morphological operations (offsetting, rounding, tightening). Segmentation. Similarity measures, comparison, variability statistics.
Machine Learning: Deep neural models. Learning, Genetic and Evolutionary Algorithms. Optimization. Deep Generative Models. Reinforcement Learning. Deep Shape Analysis, Processing, and Generation.
Point clouds: Analysis. Segmentation, Reconstruction, Interpolation. Multi-resolution. Rendering. Segmentation. Separation.
Simulation: Collision and friction. Articulated and flexible shapes. Physically based behavior. Cloth. Crowds and flocks. Deposition, erosion, and biological growth. Fluid. Hair. Viscoelastic deformations. Sound.
Hardware Acceleration: Collision and visibility queries. Frame buffer algorithms. GPUs and parallelization. Model Acquisition and Scanning.
Model Dissemination: Shared models. Collaborative access. Geometry compression. Progressive/selective refinements. Streaming scenes and animations. Watermarking. Data bases.
Application: Manufacturing. Robotics. Architecture and urban simulation. Medicine. Biology. Natural phenomena. Cinema. Videogames. Education. Cultural Heritage. Typography. Scientific Computing.
Graphical Models (GMOD) is internationally recognized as a highly rated, top-tier journal and is focused on the creation, geometric processing, animation, and visualization of graphical and geometric models and on their applications in engineering, science, culture, and entertainment. GMOD …
From January 1, 2023, Graphical Models will become a full gold open access journal freely available for everyone to access and read. All articles submitted after September 15, 2022, are subject to an article publishing charge (APC) after peer review and acceptance. Learn more about hybrid journals moving to open access. In addition to this, we are happy to share that from September 2022 Graphics and Visual Computing has merged with Graphical Models.
