- BASNet: Boundary Aware Salient Object Detection
 - SE2Net: Siamese Edge-Enhancement Network for Salient Object Detection
 - Salient Object Detection: A Survey
 - CVPR2019的显著性文章一览
 - Salient Object Detection with Pyramid Attention and Salient Edges
 - Learning Uncertain Convolutional Features for Accurate Saliency Detection
 - Attentive Feedback Network for Boundary-Aware Salient Object Detection
 - MEnet: A Metric Expression Network for Salient Object Segmentation
 - Cascaded Partial Decoder for Fast and Accurate Salient Object Detection
 - Learning to Promote Saliency Detectors
 - Pyramid Feature Attention Network for Saliency detection
 - Learning to Detect Salient Objects with Image-level Supervision
 - Deeply Supervised Salient Object Detection with Short Connections
 - A Simple Pooling-Based Design for Real-Time Salient Object Detection
 - Saliency Detection with Recurrent Fully Convolutional Networks
 - An Iterative and Cooperative Top-down and Bottom-up Inference Network for Salient Object Detection
 - A Mutual Learning Method for Salient Object Detection with intertwined Multi-Supervision
 - ICCV2019的显著性文章一览
 - ICNet: Intra-saliency Correlation Network for Co-Saliency Detection
 - Re-thinking Co-Salient Object Detection
 - CVPR2020的显著性文章一览
 - Global Context-Aware Progressive Aggregation Network for Salient Object Detection
 - F3Net: Fusion, Feedback and Focus for Salient Object Detection
 - Progressive Feature Polishing Network for Salient Object Detection
 - Towards High-Resolution Salient Object Detection
 - Selectivity or Invariance: Boundary-Aware Salient Object Detection
 - Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion
 - 一些之前的论文
 - SAC-Net: Spatial Attenuation Contextfor Salient Object Detection
 - Semi-Supervised Video Salient Object Detection Using Pseudo-Labels
 - Contour Loss: Boundary-Aware Learning for Salient Object Segmentation
 - CVPR2018的显著性文章一览
 - A Bi-directional Message Passing Model for Salient Object Detection
 - Detect Globally, Refine Locally: A Novel Approach to Saliency Detection
 
