Siamese neural networks: An overview
D Chicco - Artificial neural networks, 2021 - Springer
Similarity has always been a key aspect in computer science and statistics. Any time two
element vectors are compared, many different similarity approaches can be used …
element vectors are compared, many different similarity approaches can be used …
A review of multimodal image matching: Methods and applications
Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …
similar structure/content from two or more images that are of significant modalities or …
Image matching from handcrafted to deep features: A survey
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 …
then correspond the same or similar structure/content from two or more images. Over the …
[PDF][PDF] Soft tissue feature tracking based on deep matching network
Research in the field of medical image is an important part of the medical robot to operate
human organs. A medical robot is the intersection of multi-disciplinary research fields, in …
human organs. A medical robot is the intersection of multi-disciplinary research fields, in …
D2-net: A trainable cnn for joint description and detection of local features
In this work we address the problem of finding reliable pixel-level correspondences under
difficult imaging conditions. We propose an approach where a single convolutional neural …
difficult imaging conditions. We propose an approach where a single convolutional neural …
Image matching across wide baselines: From paper to practice
We introduce a comprehensive benchmark for local features and robust estimation
algorithms, focusing on the downstream task—the accuracy of the reconstructed camera …
algorithms, focusing on the downstream task—the accuracy of the reconstructed camera …
Receptive field block net for accurate and fast object detection
Current top-performing object detectors depend on deep CNN backbones, such as ResNet-
101 and Inception, benefiting from their powerful feature representations but suffering from …
101 and Inception, benefiting from their powerful feature representations but suffering from …
D2-net: A trainable cnn for joint detection and description of local features
In this work we address the problem of finding reliable pixel-level correspondences under
difficult imaging conditions. We propose an approach where a single convolutional neural …
difficult imaging conditions. We propose an approach where a single convolutional neural …
LF-Net: Learning local features from images
We present a novel deep architecture and a training strategy to learn a local feature pipeline
from scratch, using collections of images without the need for human supervision. To do so …
from scratch, using collections of images without the need for human supervision. To do so …
Sosnet: Second order similarity regularization for local descriptor learning
Despite the fact that Second Order Similarity (SOS) has been used with significant success
in tasks such as graph matching and clustering, it has not been exploited for learning local …
in tasks such as graph matching and clustering, it has not been exploited for learning local …