Understanding design collaboration between designers and artificial intelligence: a systematic literature review
Recent interest in design through the artificial intelligence (AI) lens is rapidly increasing.
Designers, as a special user group interacting with AI, have received more attention in the …
Designers, as a special user group interacting with AI, have received more attention in the …
A review of digital terrain modeling
Terrains are a crucial component of three‐dimensional scenes and are present in many
Computer Graphics applications. Terrain modeling methods focus on capturing landforms in …
Computer Graphics applications. Terrain modeling methods focus on capturing landforms in …
Sdedit: Guided image synthesis and editing with stochastic differential equations
Guided image synthesis enables everyday users to create and edit photo-realistic images
with minimum effort. The key challenge is balancing faithfulness to the user input (eg, hand …
with minimum effort. The key challenge is balancing faithfulness to the user input (eg, hand …
Styleflow: Attribute-conditioned exploration of stylegan-generated images using conditional continuous normalizing flows
High-quality, diverse, and photorealistic images can now be generated by unconditional
GANs (eg, StyleGAN). However, limited options exist to control the generation process using …
GANs (eg, StyleGAN). However, limited options exist to control the generation process using …
Swapping autoencoder for deep image manipulation
Deep generative models have become increasingly effective at producing realistic images
from randomly sampled seeds, but using such models for controllable manipulation of …
from randomly sampled seeds, but using such models for controllable manipulation of …
Deep fluids: A generative network for parameterized fluid simulations
This paper presents a novel generative model to synthesize fluid simulations from a set of
reduced parameters. A convolutional neural network is trained on a collection of discrete …
reduced parameters. A convolutional neural network is trained on a collection of discrete …
Llmr: Real-time prompting of interactive worlds using large language models
We present Large Language Model for Mixed Reality (LLMR), a framework for the real-time
creation and modification of interactive Mixed Reality experiences using LLMs. LLMR …
creation and modification of interactive Mixed Reality experiences using LLMs. LLMR …
Spatial interpolation using conditional generative adversarial neural networks
Spatial interpolation is a traditional geostatistical operation that aims at predicting the
attribute values of unobserved locations given a sample of data defined on point supports …
attribute values of unobserved locations given a sample of data defined on point supports …
Generative adversarial networks–enabled human–artificial intelligence collaborative applications for creative and design industries: A systematic review of current …
The future of work and workplace is very much in flux. A vast amount has been written about
artificial intelligence (AI) and its impact on work, with much of it focused on automation and …
artificial intelligence (AI) and its impact on work, with much of it focused on automation and …
Learning to generate 3d shapes from a single example
Existing generative models for 3D shapes are typically trained on a large 3D dataset, often
of a specific object category. In this paper, we investigate the deep generative model that …
of a specific object category. In this paper, we investigate the deep generative model that …