RGB Salient Object Detection

90 papers with code • 14 benchmarks • 16 datasets

RGB Salient object detection is a task-based on a visual attention mechanism, in which algorithms aim to explore objects or regions more attentive than the surrounding areas on the scene or RGB images.

( Image credit: Attentive Feedback Network for Boundary-Aware Salient Object Detection )


Use these libraries to find RGB Salient Object Detection models and implementations

Most implemented papers

U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection

NathanUA/U-2-Net 18 May 2020

In this paper, we design a simple yet powerful deep network architecture, U$^2$-Net, for salient object detection (SOD).

Res2Net: A New Multi-scale Backbone Architecture

open-mmlab/mmdetection 2 Apr 2019

We evaluate the Res2Net block on all these models and demonstrate consistent performance gains over baseline models on widely-used datasets, e. g., CIFAR-100 and ImageNet.

RGB-D Salient Object Detection: A Survey

taozh2017/RGBD-SODsurvey 1 Aug 2020

Further, considering that the light field can also provide depth maps, we review SOD models and popular benchmark datasets from this domain as well.

A Simple Pooling-Based Design for Real-Time Salient Object Detection

backseason/PoolNet CVPR 2019

We further design a feature aggregation module (FAM) to make the coarse-level semantic information well fused with the fine-level features from the top-down pathway.

EGNet: Edge Guidance Network for Salient Object Detection

JXingZhao/EGNet ICCV 2019

In the second step, we integrate the local edge information and global location information to obtain the salient edge features.

F3Net: Fusion, Feedback and Focus for Salient Object Detection

weijun88/F3Net 26 Nov 2019

Furthermore, different from binary cross entropy, the proposed PPA loss doesn't treat pixels equally, which can synthesize the local structure information of a pixel to guide the network to focus more on local details.

Uncertainty Inspired RGB-D Saliency Detection

JingZhang617/UCNet 7 Sep 2020

Our framework includes two main models: 1) a generator model, which maps the input image and latent variable to stochastic saliency prediction, and 2) an inference model, which gradually updates the latent variable by sampling it from the true or approximate posterior distribution.

Reverse Attention for Salient Object Detection

ShuhanChen/RAS_ECCV18 ECCV 2018

Benefit from the quick development of deep learning techniques, salient object detection has achieved remarkable progresses recently.

BASNet: Boundary-Aware Salient Object Detection

NathanUA/BASNet CVPR 2019

In this paper, we propose a predict-refine architecture, BASNet, and a new hybrid loss for Boundary-Aware Salient object detection.

CAGNet: Content-Aware Guidance for Salient Object Detection

Mehrdad-Noori/Saliency-Evaluation-Toolbox 29 Nov 2019

Beneficial from Fully Convolutional Neural Networks (FCNs), saliency detection methods have achieved promising results.