Finding correspondences between images is a fundamental problem in computer vision. In
this paper, we show that correspondence emerges in image diffusion models without any …

A point cloud as a collection of points is poised to bring about a revolution in acquiring and
generating three‐dimensional (3D) surface information of an object in 3D reconstruction …

Text-to-image diffusion models have made significant advances in generating and editing
high-quality images. As a result, numerous approaches have explored the ability of diffusion …

This paper presents a novel cost aggregation network, called Volumetric Aggregation with
Transformers (VAT), for few-shot segmentation. The use of transformers can benefit …

This paper presents a simple yet effective approach to modeling space-time
correspondences in the context of video object segmentation. Unlike most existing …

We introduce a self-supervised method for learning visual correspondence from unlabeled
video. The main idea is to use cycle-consistency in time as free supervisory signal for …

We address the problem of finding reliable dense correspondences between a pair of
images. This is a challenging task due to strong appearance differences between the …

We address the problem of determining correspondences between two images in
agreement with a geometric model such as an affine or thin-plate spline transformation, and …

Most existing studies on learning local features focus on the patch-based descriptions of
individual keypoints, whereas neglecting the spatial relations established from their keypoint …

In recent years, building change detection has made remarkable progress through using
deep learning. The core problems of this technique are the need for additional data (eg …