Designing and generating new data under targeted properties has been attracting various
critical applications such as molecule design, image editing and speech synthesis …

Text-to-image synthesis has recently seen significant progress thanks to large pretrained
language models, large-scale training data, and the introduction of scalable model families …

Accurate and controllable image editing is a challenging task that has attracted significant
attention recently. Notably DragGAN developed by Pan et al.(2023) is an interactive point …

Recent years have seen remarkable progress in deep learning powered visual content
creation. This includes deep generative 3D-aware image synthesis, which produces high …

Synthesizing visual content that meets users' needs often requires flexible and precise
controllability of the pose, shape, expression, and layout of the generated objects. Existing …

We introduce a high resolution, 3D-consistent image and shape generation technique which
we call StyleSDF. Our method is trained on single view RGB data only, and stands on the …

Diffusion probabilistic models (DPMs) have achieved remarkable quality in image
generation that rivals GANs'. But unlike GANs, DPMs use a set of latent variables that lack …

Can a generative model be trained to produce images from a specific domain, guided only
by a text prompt, without seeing any image? In other words: can an image generator be …

We observe that despite their hierarchical convolutional nature, the synthesis process of
typical generative adversarial networks depends on absolute pixel coordinates in an …

The inversion of real images into StyleGAN's latent space is a well-studied problem.
Nevertheless, applying existing approaches to real-world scenarios remains an open …