Learning Hierarchical Features for Scene Labeling
基本情況 這是PAMI2013的一篇文章，作者是LeCun等人，所屬領域是Image Segmentation. Abstract 本文提出了一種多尺度CNN，並且結合超像素的最佳覆蓋，實現語義分割。在Sift Flow（33類）和Barcelona DataSet （170類）打破記錄，在Stanford Background Dataset（8類）接近記錄。產生320 ×240圖像標籤不到一秒
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相關文章
- 1. Learning Hierarchical Features for Scene Labeling
- 2. 論文理解 A Bayesian Hierarchical Model for Learning Natural Scene Categories
- 3. Hierarchical Features Driven Residual Learning for Depth Map Super-Resolution 2019TIP 論文閱讀
- 4. [論文筆記]Learning Deep Features for Scene Recognition using Places Database
- 5. Latent Space Policies for Hierarchical Reinforcement Learning
- 6. Automatically Learning Semantic Features for Defect Prediction
- 7. Learning Region Features for Object Detection
- 8. Learning Deep Features for Discriminative Localization
- 9. 【ReID】Hierarchical and Efficient Learning for Person Re-Identification
- 10. Face_Parsing_2016-master（Multi-Objective Convolutional Learning for Face Labeling）