We propose a Lagrangian particle-based formulation for simulating deformation, fracture, and diffusion in thin membranelike structures, such as aluminium foil, rubbery films, and seaweed flakes. We integrate our model with ...

Photon mapping is a light transport algorithm that simulates various rendering effects (e.g., caustics) robustly, and its progressive variants, progressive photon mapping (PPM) methods, can produce a biased but consistent ...

To exploit the potential of immersive network analytics for engaging and effective exploration, we promote the metaphor of ''egocentrism'', where data depiction and interaction are adapted to the perspective of the user ...

The representation of geometric models by trimmed NURBS surfaces has become a standard in the CAD industry. In CAD applications, the rendering of surfaces is usually solved by tessellation followed up by z-buffer rendering. ...

While convolutional neural networks (CNNs) have found wide adoption as state-of-the-art models for image-related tasks, their predictions are often highly sensitive to small input perturbations, which the human vision is ...

An effective fragment merging technique is presented in this study that addresses multi-fragment problems, including fragment overflow and z-fighting, and provides visual effects that are beneficial for various screen-space ...

Traditional approaches to retarget existing facial blendshape animations to other characters rely heavily on manually paired data including corresponding anchors, expressions, or semantic parametrizations to preserve the ...

Path tracing has been used for real-time renderings, thanks to the powerful GPU device. Unfortunately, path tracing produces noisy rendered results, thus, filtering or denoising is often applied as a post-process to remove ...

We introduce Seamless Satellite-image Synthesis (SSS), a novel neural architecture to create scale-and-space continuous satellite textures from cartographic data. While 2D map data is cheap and easily synthesized, accurate ...

The modern supervised approaches for human image relighting rely on training data generated from 3D human models. However, such datasets are often small (e.g., Light Stage data with a small number of individuals) or limited ...