Dream lens: Exploration and visualization of large-scale generative design datasets
This paper presents Dream Lens, an interactive visual analysis tool for exploring and
visualizing large-scale generative design datasets. Unlike traditional computer aided …
visualizing large-scale generative design datasets. Unlike traditional computer aided …
Sequential gallery for interactive visual design optimization
Visual design tasks often involve tuning many design parameters. For example, color
grading of a photograph involves many parameters, some of which non-expert users might …
grading of a photograph involves many parameters, some of which non-expert users might …
Sequential line search for efficient visual design optimization by crowds
Parameter tweaking is a common task in various design scenarios. For example, in color
enhancement of photographs, designers tweak multiple parameters such as" brightness" …
enhancement of photographs, designers tweak multiple parameters such as" brightness" …
An intuitive control space for material appearance
Many different techniques for measuring material appearance have been proposed in the
last few years. These have produced large public datasets, which have been used for …
last few years. These have produced large public datasets, which have been used for …
BO as assistant: Using Bayesian optimization for asynchronously generating design suggestions
Many design tasks involve parameter adjustment, and designers often struggle to find
desirable parameter value combinations by manipulating sliders back and forth. For such a …
desirable parameter value combinations by manipulating sliders back and forth. For such a …
TypeDance: Creating semantic typographic logos from image through personalized generation
Semantic typographic logos harmoniously blend typeface and imagery to represent
semantic concepts while maintaining legibility. Conventional methods using spatial …
semantic concepts while maintaining legibility. Conventional methods using spatial …
Human-in-the-loop differential subspace search in high-dimensional latent space
CH Chiu, Y Koyama, YC Lai, T Igarashi… - ACM Transactions on …, 2020 - dl.acm.org
Generative models based on deep neural networks often have a high-dimensional latent
space, ranging sometimes to a few hundred dimensions or even higher, which typically …
space, ranging sometimes to a few hundred dimensions or even higher, which typically …
Geppetto: Enabling semantic design of expressive robot behaviors
Expressive robots are useful in many contexts, from industrial to entertainment applications.
However, designing expressive robot behaviors requires editing a large number of …
However, designing expressive robot behaviors requires editing a large number of …
Procedural modeling using autoencoder networks
Procedural modeling systems allow users to create high quality content through parametric,
conditional or stochastic rule sets. While such approaches create an abstraction layer by …
conditional or stochastic rule sets. While such approaches create an abstraction layer by …
Artinter: AI-Powered Boundary Objects for Commissioning Visual Arts
When commissioning visual art, clients and artists communicate to agree on what is to be
created. This often requires bridging a language gap in how they conceive art. To arrive at a …
created. This often requires bridging a language gap in how they conceive art. To arrive at a …