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 …

Semantic image segmentation, which becomes one of the key applications in image
processing and computer vision domain, has been used in multiple domains such as …

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 …

The primary method of endoscopic image mosaics seamlessly mosaics several continuous
and overlapping endoscopic images to have a broader vision and clearer images. The key …

We introduce a comprehensive benchmark for local features and robust estimation
algorithms, focusing on the downstream task—the accuracy of the reconstructed camera …

Object detection generally requires sliding-window classifiers in tradition or anchor-based
predictions in modern deep learning approaches. However, either of these approaches …

Ship classification in synthetic aperture radar (SAR) images is a fundamental and significant
step in ocean surveillance. Recently, with the rise of deep learning (DL), modern abstract …

Traditional feature matching methods, such as scale-invariant feature transform (SIFT),
usually use image intensity or gradient information to detect and describe feature points; …

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 …

In this paper, we present a large-scale Diverse Real-world image Super-Resolution dataset,
ie, DRealSR, as well as a divide-and-conquer Super-Resolution (SR) network, exploring the …