Video instance segmentation is a challenging task that extends image instance
segmentation to the video domain. Existing methods either rely only on single-frame …

The crux of self-supervised video representation learning is to build general features from
unlabeled videos. However, most recent works have mainly focused on high-level semantics …

Distance estimation using a monocular camera is one of the most classic tasks for computer
vision. Current monocular distance estimating methods need a lot of data collection or they …

Symmetric encryption algorithms enable rapid encryption of data in IoT based supply chains,
which helps to alleviate the concerns of supply chain participants about privacy disclosure …

The purpose of this study is to propose a framework for accurate and efficient vehicle
distance estimation from a monocular camera. The proposed framework consists of a …

A primary challenge faced in few-shot action recognition is inadequate video data for
training. To address this issue, current methods in this field mainly focus on devising …

Existing saliency prediction methods focus on exploring a universal saliency model for
natural images, relatively few on advertising images which typically consists of both textual …

Current few-shot action recognition involves two primary sources of information for
classification:(1) intra-video information, determined by frame content within a single video …

Object detection is an essential and impactful technology in various fields due to its ability to
automatically locate and identify objects in images or videos. In addition, object-distance …

Utilizing a single camera for measuring object distances is a cost-effective alternative to
stereo-vision and LiDAR. Although monocular distance estimation has been explored in the …