Event-based cameras bring a unique capability to tracking, being able to function in
challenging real-world conditions as a direct result of their high temporal resolution and high …

The learning-based methods for single image super-resolution (SISR) can reconstruct
realistic details, but they suffer severe performance degradation for low-light images …

Most existing RGB-based trackers target low frame rate benchmarks of around 30 frames
per second. This setting restricts the tracker's functionality in the real world, especially for fast …

In this paper, we propose a novel two-stage context-aware network named CANet for
shadow removal, in which the contextual information from non-shadow regions is transferred …

Super-resolution (SR) is an ill-posed inverse problem where the size of the set of feasible
solutions that are consistent with a given low-resolution image is very large. Many …

Existing image captioning methods just focus on understanding the relationship between
objects or instances in a single image, without exploring the contextual correlation existed …

Glass is very common in the real world. Influenced by the uncertainty about the glass region
and the varying complex scenes behind the glass, the existence of glass poses severe …

Deep convolutional neural networks (CNNs) have demonstrated tremendous success in
image super-resolution (SR). According to the frequency principle, the vanilla CNNs fit the …

Ground penetrating radar (GPR) has been commonly applied for the non-destructive
investigation of underground anomalies. This study proposes a robust anomaly detection …

Image interpolation is the process of transforming a low-resolution image into a higher-
resolution image of a different size. The current study analyzes several picture interpolation …