Xfeat: Accelerated features for lightweight image matching

G Potje, F Cadar, A Araujo, R Martins… - Proceedings of the …, 2024 - openaccess.thecvf.com
We introduce a lightweight and accurate architecture for resource-efficient visual
correspondence. Our method dubbed XFeat (Accelerated Features) revisits fundamental …

Local feature matching using deep learning: A survey

S Xu, S Chen, R Xu, C Wang, P Lu, L Guo - Information Fusion, 2024 - Elsevier
Local feature matching enjoys wide-ranging applications in the realm of computer vision,
encompassing domains such as image retrieval, 3D reconstruction, and object recognition …

MSGM: An advanced deep multi-size guiding matching network for whole slide histopathology images addressing staining variation and low visibility challenges

X Li, Z Li, T Hu, M Long, X Ma, J Huang… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Matching whole slide histopathology images to provide comprehensive information on
homologous tissues is beneficial for cancer diagnosis. However, the challenge arises with …

Learned Good Features to Track

Y Lin, Y Jiang, X Jiao, B Han - IEEE Transactions on Circuits …, 2024 - ieeexplore.ieee.org
Tracking features in image sequences suffers from varying illumination and viewpoints. In
recent years, learning-based features have achieved higher repeatability in challenging …

Perturbation defense ultra high-speed weak target recognition

B Xue, Q Zheng, Z Li, J Wang, C Mu, J Yang… - … Applications of Artificial …, 2024 - Elsevier
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 …

Self-supervised fusion network for RGB-D interest point detection and description

N Li, X Wang, Z Zheng, Z Sun - Pattern Recognition, 2025 - Elsevier
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 by Jointly Semantic-guided and Task Rewards

L Wang, Y Zhang, F Ge, W Bai… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
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 …

Residual Learning for Image Point Descriptors

R Shrestha, A Chhatkuli, M Kanakis… - arxiv preprint arxiv …, 2023 - arxiv.org
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 …