Learning Hierarchical Features for Scene Labeling
基本情况 这是PAMI2013的一篇文章，作者是LeCun等人，所属领域是Image Segmentation. Abstract 本文提出了一种多尺度CNN，并且结合超像素的最佳覆盖，实现语义分割。在Sift Flow（33类）和Barcelona DataSet （170类）打破记录，在Stanford Background Dataset（8类）接近记录。产生320 ×240图像标签不到一秒
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相关文章
- 1. Learning Hierarchical Features for Scene Labeling
- 2. 论文理解 A Bayesian Hierarchical Model for Learning Natural Scene Categories
- 3. Hierarchical Features Driven Residual Learning for Depth Map Super-Resolution 2019TIP 论文阅读
- 4. [论文笔记]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）