Shape-Former: Bridging CNN and Transformer via ShapeConv for multimodal image matching
As with any data fusion task, the front-end of the pipeline for image fusion, aiming to collect
multitudinous physical properties from multimodal images taken by different types of …
multitudinous physical properties from multimodal images taken by different types of …
3dregnet: A deep neural network for 3d point registration
We present 3DRegNet, a novel deep learning architecture for the registration of 3D scans.
Given a set of 3D point correspondences, we build a deep neural network to address the …
Given a set of 3D point correspondences, we build a deep neural network to address the …
Samaug: Point prompt augmentation for segment anything model
This paper introduces SAMAug, a novel visual point augmentation method for the Segment
Anything Model (SAM) that enhances interactive image segmentation performance …
Anything Model (SAM) that enhances interactive image segmentation performance …
Feature dynamic alignment and refinement for infrared–visible image fusion: Translation robust fusion
Translational displacement between source images from different sensors is a general
phenomenon, which will cause performance degradation on image fusion. To tackle this …
phenomenon, which will cause performance degradation on image fusion. To tackle this …
Robust feature matching using spatial clustering with heavy outliers
This paper focuses on removing mismatches from given putative feature matches created
typically based on descriptor similarity. To achieve this goal, existing attempts usually …
typically based on descriptor similarity. To achieve this goal, existing attempts usually …
A two-step descriptor-based keypoint filtering algorithm for robust image matching
Finding robust and correct keypoints in images remains a challenge, especially when
repetitive patterns are present. In this article, we propose a universal two-step filtering …
repetitive patterns are present. In this article, we propose a universal two-step filtering …