Generative transformers have experienced rapid popularity growth in the computer vision
community in synthesizing high-fidelity and high-resolution images. The best generative …

This paper develops a unified framework for image-to-image translation based on
conditional diffusion models and evaluates this framework on four challenging image-to …

GAN inversion aims to invert a given image back into the latent space of a pretrained GAN
model so that the image can be faithfully reconstructed from the inverted code by the …

Advancing image inpainting is challenging as it requires filling user-specified regions for
various intents, such as background filling and object synthesis. Existing approaches focus …

Recent years have witnessed the rapid progress of generative adversarial networks (GANs).
However, the success of the GAN models hinges on a large amount of training data. This …

Recent advances in diffusion models have successfully enabled text-guided image
inpainting. While it seems straightforward to extend such editing capability into the video …

We present" SemCity" a 3D diffusion model for semantic scene generation in real-world
outdoor environments. Most 3D diffusion models focus on generating a single object …

Modern 3D-GANs synthesize geometry and texture by training on large-scale datasets with
a consistent structure. Training such models on stylized, artistic data, with often unknown …

Generative models operate at fixed resolution, even though natural images come in a variety
of sizes. As high-resolution details are downsampled away and low-resolution images are …

Panorama video recently attracts more interest in both study and application courtesy of its
immersive experience. Due to the expensive cost of capturing 360-degree panoramic videos …