Conventional neural networks have been demonstrated to be a powerful framework for
background subtraction in video acquired by static cameras. Indeed, the well-known Self …

This tutorial reviews image alignment and image stitching algorithms. Image alignment
algorithms can discover the correspondence relationships among images with varying …

A neural radiance field (NeRF) is a scene model supporting high-quality view synthesis,
optimized per scene. In this paper, we explore enabling user editing of a category-level …

Large scale text-guided diffusion models have garnered significant attention due to their
ability to synthesize diverse images that convey complex visual concepts. This generative …

Traditional feature-based image stitching technologies rely heavily on feature detection
quality, often failing to stitch images with few features or low resolution. The learning-based …

Traditional image stitching approaches tend to leverage increasingly complex geometric
features (point, line, edge, etc.) for better performance. However, these hand-crafted features …

This paper studies a combination of generative Markov random field (MRF) models and
discriminatively trained deep convolutional neural networks (dCNNs) for synthesizing 2D …

We extend neural 3D representations to allow for intuitive and interpretable user control
beyond novel view rendering (ie camera control). We allow the user to annotate which part …

Numerous single image blind deblurring algorithms have been proposed to restore latent
sharp images under camera motion. However, these algorithms are mainly evaluated using …

It is common but challenging to address high-resolution image blending in the automatic
photo editing application. In this paper, we would like to focus on solving the problem of high …