Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR)
image from a low-resolution (LR) observation, has been an active research topic in the area …

Super resolution (SR) is an eminent system in the field of computer vison and image
processing to improve the visual perception of the poor-quality images. The key objective of …

Few-shot semantic segmentation aims at learning to segment a target object from a query
image using only a few annotated support images of the target class. This challenging task …

Accurately and timely detecting multiscale small objects that contain tens of pixels from
remote sensing images (RSI) remains challenging. Most of the existing solutions primarily …

This research focuses on the discovery and localization of hidden objects in the wild and
serves unmanned systems. Through empirical analysis, infrared and visible image fusion …

The detection of small infrared targets with low signal-to-noise ratios (SNRs) and contrasts in
noisy and cluttered backgrounds is challenging and therefore a domain of active research …

We propose a novel end-to-end learning-based approach for single image defocus
deblurring. The proposed approach is equipped with a novel Iterative Filter Adaptive …

The contextual information plays a core role in semantic segmentation. As for video
semantic segmentation, the contexts include static contexts and motional contexts …

Whether what you see in Figure 1 is a" flamingo" or a" bird", is the question we ask in this
paper. While fine-grained visual classification (FGVC) strives to arrive at the former, for the …

Capturing images has been increasingly popular in recent years, owing to the widespread
availability of cameras. Images are essential in our daily lives because they contain a wealth …