With the emergence of deep learning, computer vision has witnessed extensive
advancement and has seen immense applications in multiple domains. Specifically, image …

Semantic segmentation of aerial videos has been extensively used for decision making in
monitoring environmental changes, urban planning, and disaster management. The …

Scene understanding through pixel-level semantic parsing is one of the main problems in
computer vision. Till now, image-based methods and datasets for scene parsing have been …

We propose a novel neural network module that transforms an existing single-frame
semantic segmentation model into a video semantic segmentation pipeline. In contrast to …

Video object segmentation's primary goal is to automatically extract the principal object (s) in
the foreground from the background in videos. The primary focus of the current deep …

Weakly supervised multi-class video segmentation is one of the most challenging yet least
studied research problems in computer vision. This study aims to investigate two main …

The patients and surgeons are usually exposed in massive ionizing radiation during
fluoroscopy-based navigation orthopedic surgery. Comparatively, ultrasound-assisted …

The per-frame segmentation methods have a high computational cost, thereby, these
methods are insufficient to cope with the fast inference need of semantic video …

Video object segmentation aims at separating foreground object from background, and it is
far from well solved for different challenges such as deformation, occlusion and motion blurs …

Image scene analysis is to analyze image scene content through image semantic
segmentation, which can identify the categories and positions of different objects in an …