Image inpainting aims to restore the pixel features of damaged parts in incomplete image
and plays a key role in many computer vision tasks. Image inpainting technology based on …

Spectral super-resolution (sSR) is a very important technique to obtain hyperspectral images
from only RGB images, which can effectively overcome the high acquisition cost and low …

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 …

Many interesting tasks in image restoration can be cast as linear inverse problems. A recent
family of approaches for solving these problems uses stochastic algorithms that sample from …

Image restoration tasks demand a complex balance between spatial details and high-level
contextualized information while recovering images. In this paper, we propose a novel …

Large-scale text-to-image generative models have shown their remarkable ability to
synthesize diverse, high-quality images. However, directly applying these models for real …

We present a novel approach to leverage prior knowledge encapsulated in pre-trained text-
to-image diffusion models for blind super-resolution. Specifically, by employing our time …

We present DiffBIR, a general restoration pipeline that could handle different blind image
restoration tasks in a unified framework. DiffBIR decouples blind image restoration problem …

We present CLIP-NeRF, a multi-modal 3D object manipulation method for neural radiance
fields (NeRF). By leveraging the joint language-image embedding space of the recent …

The tremendous progress in neural image generation, coupled with the emergence of
seemingly omnipotent vision-language models has finally enabled text-based interfaces for …