Recent advances in diffusion models have set an impressive milestone in many generation
tasks, and trending works such as DALL-E2, Imagen, and Stable Diffusion have attracted …

Recently, CLIP-guided image synthesis has shown appealing performance on adapting a
pre-trained source-domain generator to an unseen target domain. It does not require any …

In recent years, many deep learning based image inpainting methods have been developed
by the research community. Some of those methods have shown impressive image …

Recently diffusion models have made remarkable progress in text-to-image (T2I) generation
synthesizing images with high fidelity and diverse contents. Despite this advancement latent …

As the development of the Internet of Things (IoT), the security of images in social networks
is attracting more and more attention. Among the various encryption methods, thumbnail …

Wires and powerlines are common visual distractions that often undermine the aesthetics of
photographs. The manual process of precisely segmenting and removing them is extremely …

Abstract We present Zero-Painter a novel training-free framework for layout-conditional text-
to-image synthesis that facilitates the creation of detailed and controlled imagery from textual …

Super-resolution (SR) neural networks have recently achieved great progress in restoring
high-quality remote sensing images (RSIs) at low zoom-in magnitudes. However, these …

We present a novel coarser-to-finer approach for deep graphical image inpainting that
utilizes GraphFill, a graph neural network-based deep learning framework, and a lightweight …

Existing conditional generation models using generative adversarial networks (GANs) suffer
from two common limitations: 1) they heavily rely on supervision, or 2) their performance is …