A content-aware guidance network for salient object detection is introduced. The diverse recognition abilities of multi-level features are exploited to guide�...

Nov 29, 2019 � We propose a Feature Guide Network which exploits the nature of low-level and high-level features to i) make foreground and background regions more distinct.

This repository contains the Tensorflow implementation of our paper "CAGNet: Content-Aware Guidance for Salient Object Detection".

Salient object detection aims at localizing the most interesting and prominent parts of an image. Moreover, it is an effective pre-processing step for numerous�...

This work proposes leveraging on the extraction of finer semantic features from multiple encoding layers and attentively re-utilize it in the generation of�...

This repository contains measures for evaluating salient object detection models in python. Requirements Usage Simply import calculate_measures.

Saliency Detection is a preprocessing step in computer vision which aims at finding salient objects in an image.

The overall architecture of our proposed Content-Aware Guidance Network (CAGNet). CAGNet consists of three networks: (i) Feature Extraction Network which�...

Apr 17, 2024 � We propose a sophisticated context-aware middle-layer guidance network (CMGNet). CMGNet incorporates the context-aware central-layer guidance module (CCGM).

CAGNet: Content-Aware Guidance for Salient Object Detection ... Beneficial from Fully Convolutional Neural Networks (FCNs), saliency detection methods have�...