Focal Boundary Guided Salient Object Detection


The use of deep convolutional networks has significantly improved the performance of salient object segmentation. However, these networks often yield blob-like maps of saliency that do not accurately represent the boundaries of individual objects. After several pooling procedures, their feature maps have a restricted spatial resolution, which may impede downstream applications that demand precise object forms. A unique deep model-Focal Boundary Guided (Focal-BG) network is proposed to overcome this problem. Salient object masks are segmented using our model, while salient object borders are detected using our model's algorithm. We believe that extra information regarding the borders of an object can aid in the exact identification of the object's shape. A refinement process for mask prediction and the usage of the focus loss in the learning of hard boundary pixels are also included in our model. We run a wide range of experiments to test our model. This network routinely surpasses the state of the art approaches in five important benchmarks. In our extensive research, we show that our joint modelling of salient object boundaries and masks helps to better capture the form features, particularly in the vicinity of object boundaries.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Residual Learning for Salient Object Detection ABSTRACT: Most recently developed salient object detection deep learning algorithms use multi-scale methodologies and fully convolutional neural networks to enhance
PROJECT TITLE : Reverse Attention-Based Residual Network for Salient Object Detection ABSTRACT: Recent advances in salient object detection have been made thanks to the rapid development of deep convolutional neural networks,
PROJECT TITLE : RGB-T Salient Object Detection via Fusing Multi-Level CNN Features ABSTRACT: Deep convolutional neural networks have lately made significant progress in the field of RGB-inducing salient object recognition (CNNs).
PROJECT TITLE : Salient Object Detection With Lossless Feature Reflection and Weighted Structural Loss ABSTRACT: As more and more real-world applications emerge, salient object identification, which tries to identify and find
PROJECT TITLE : Semantic Prior Analysis for Salient Object Detection ABSTRACT: The goal of salient item recognition is to identify the image's most important elements. Semantic priors are integrated into the salient object recognition

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry