总结 ICCV 2019显著性目标检测文章

总结 ICCV 2019显著性目标检测文章

1. Employing Deep Part-Object Relationships for Salient Object Detection
2. TASED-Net: Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency Detection
3. Structured Modeling of Joint Deep Feature and Prediction Refinement for Salient Object Detection
4. Selectivity or Invariance: Boundary-Aware Salient Object Detection
5. Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation
6. Towards High-Resolution Salient Object Detection
7. Depth-Induced Multi-Scale Recurrent Attention Network for Saliency Detection
8. Stacked Cross Refinement Network for Edge-Aware Salient Object Detection
9. Motion Guided Attention for Video Salient Object Detection
10. Semi-Supervised Video Salient Object Detection Using Pseudo-Labels
11. EGNet: Edge Guidance Network for Salient Object Detection
12. Deep Learning for Light Field Saliency Detection
13. Optimizing the F-Measure for Threshold-Free Salient Object Detection

最后

以上就是哭泣月光最近收集整理的关于总结 ICCV 2019显著性目标检测文章的全部内容，更多相关总结内容请搜索靠谱客的其他文章。