論文閱讀 - ExFuse: Enhancing Feature Fusion for Semantic Segmentation
論文閱讀 - ExFuse: Enhancing Feature Fusion for Semantic Segmentation (ECCV 2018 Fudan University, Megvii Inc.) 這篇文章研究語義分割網絡中高低層特徵融合的效率問題。在很多工作中，融合不同尺度的特徵是提高分割性能的一個重要手段。低層特徵分辨率更高，包含更多位置、細節信息，但是由於經過的卷積更少
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- 1. ExFuse- Enhancing Feature Fusion for Semantic Segmentation筆記
- 2. [深度學習論文筆記][arxiv 1804]ExFuse: Enhancing Feature Fusion for Semantic Segmentation
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相關文章
- 1. ExFuse- Enhancing Feature Fusion for Semantic Segmentation筆記
- 2. [深度學習論文筆記][arxiv 1804]ExFuse: Enhancing Feature Fusion for Semantic Segmentation
- 3. 【論文閱讀】Structured Knowledge Distillation for Semantic Segmentation
- 4. 論文閱讀：《Understanding Convolution for Semantic Segmentation》
- 5. Semantic Segmentation---DFANet:Deep Feature Aggregation for Real-Time Semantic Segmentation（論文解讀十）
- 6. 【論文閱讀】Learning Deconvolution Network for Semantic Segmentation
- 7. Semantic Soft segmentation 論文閱讀
- 8. 【論文閱讀】Rich feature hierarchies for accurate object detection and semantic segmentation
- 9. [ICCV2019論文閱讀]ACFNet: Attentional Class Feature Network for Semantic Segmentation
- 10. 【論文閱讀筆記】Rich feature hierarchies for accurate object detection and semantic segmentation