Feature refinement and feature fusion are two key steps in convolutional neural networks–based salient object detection (SOD). In this article, we investigate how to utilize multiple guidance mechanisms better refine fuse extracted multi-level features propose a novel multi-guidance SOD model dubbed as MGuid-Net. Since boundary information is beneficial for locating sharpening objects, edge uti...

Abstract Fast state-of-the-art multi-object-tracking (MOT) schemes, such as reported in challenges MOT16 and Mot20, perform tracking on a single sensor, often couple detection, support only one kind of object representation or don’t take varying latencies update rates into account. We propose fast generic MOT system for use real world applications which is capable objects from different sensor ...

Content-based image retrieval has been a hot topic among computer vision researchers for long time. There have many advances over the years, one of recent ones being deep metric learning, inspired by success neural networks in machine learning tasks. The goal is to extract good high-level features from pixel data using networks. These provide useful abstractions, which can enable algorithms per...

Abstract Conceptual modeling of domain object hierarchies, such as product hierarchies or organization is difficult due to the intricate nature nonphysical objects organized in hierarchies. Modeling part-whole covers their hierarchical structure, yet capture meaning, have be combined with specialization and multi-level instantiation. To this end we introduce deep (DDO) pattern approach. With DD...