We investigate how to generate multimodal image outputs, such as RGB, de...
Text-to-image diffusion models have advanced towards more controllable
g...
We present a lightweighted neural PDE representation to discover the hid...
Large-scale text-to-image generative models have shown their remarkable
...
We introduce a new method for diverse foreground generation with explici...
3D-controllable portrait synthesis has significantly advanced, thanks to...
In this work, we propose a complete framework that generates visual art....
Existing GAN inversion and editing methods work well for aligned objects...
Spatial transcriptomics (ST) has advanced significantly in the last few
...
We propose a new approach for high resolution semantic image synthesis. ...
Training generative models, such as GANs, on a target domain containing
...
We introduce an inversion based method, denoted as IMAge-Guided model
IN...
Extensive research in neural style transfer methods has shown that the
c...
Generative adversarial networks (GANs), e.g., StyleGAN2, play a vital ro...
Few-shot image generation seeks to generate more data of a given domain,...
Universal style transfer methods typically leverage rich representations...
Image extrapolation aims at expanding the narrow field of view of a give...
We propose a high-quality photo-to-pencil translation method with
fine-g...
Existing video prediction methods mainly rely on observing multiple
hist...
Photorealistic image style transfer algorithms aim at stylizing a conten...
Joint image filters leverage the guidance image as a prior and transfer ...
Universal style transfer aims to transfer arbitrary visual styles to con...
Recent progresses on deep discriminative and generative modeling have sh...
Time-of-Flight (ToF) depth sensing camera is able to obtain depth maps a...