Local feature matching enjoys wide-ranging applications in the realm of computer vision,
encompassing domains such as image retrieval, 3D reconstruction, and object recognition …

We introduce a lightweight and accurate architecture for resource-efficient visual
correspondence. Our method dubbed XFeat (Accelerated Features) revisits fundamental …

Matching whole slide histopathology images to provide comprehensive information on
homologous tissues is beneficial for cancer diagnosis. However, the challenge arises with …

Ultra high-speed target recognition in complex electromagnetic environments is a critical
and fundamental machine perception issue. It is difficult to ensure privacy protection and …

Interest point detection and description are highly challenging in indoor environments with
repeated and sparse textures and heavy illumination changes (noted as challenging indoor …

Learning local features is a fundamental task for many computer vision applications. Existing
methods often struggle to maintain robustness and accuracy in extracting local features …

Local image feature descriptors have had a tremendous impact on the development and
application of computer vision methods. It is therefore unsurprising that significant efforts are …

Tracking features in image sequences suffers from varying illumination and viewpoints. In
recent years, learning-based features have achieved higher repeatability in challenging …

Efficient interest point detection and description in images play a crucial role in many tasks
such as multi-robot SLAM and collaborative localization. To facilitate fast detection and …

Detection and description of keypoints in images is a fundamental component of a wide
range of tasks such as Simultaneous Localization And Mapping (SLAM), image alignment …