As a fundamental and critical task in various visual applications, image matching can identify
then correspond the same or similar structure/content from two or more images. Over the …

Generating robust and reliable correspondences across images is a fundamental task for a
diversity of applications. To capture context at both global and local granularity, we propose …

A novel image matching method is proposed that utilizes learned features extracted by an off-
the-shelf deep neural network to obtain a promising performance. The proposed method …

Image matching plays a vital role in many computer vision tasks, and this paper focuses on
the mismatch removal problem of feature-based matching. We formulate the problem into a …

Finding matching images across large datasets plays a key role in many computer vision
applications such as structure-from-motion (SfM), multi-view 3D reconstruction, image …

Line segments are powerful features complementary to points. They offer structural cues,
robust to drastic viewpoint and illumination changes, and can be present even in texture …

This paper proposes a new end-to-end trainable matching network based on receptive field,
RF-Net, to compute sparse correspondence between images. Building end-to-end trainable …

Image matching is a fundamental problem in Computer Vision. In the context of feature-
based matching, SIFT and its variants have long excelled in a wide array of applications …

Feature-based matching methods have been widely used in remote sensing image
matching given their capability to achieve excellent performance despite image geometric …

The detector-free feature matching approaches are currently attracting great attention thanks
to their excellent performance. However, these methods still struggle at large-scale and …