https://github.com/acecoooool/paper-zh

daily paper reading
https://github.com/acecoooool/paper-zh

paper zh-cn

Last synced: about 2 months ago
JSON representation

daily paper reading

• Host: GitHub
• URL: https://github.com/acecoooool/paper-zh
• Owner: AceCoooool
• Created: 2018-01-02T14:32:49.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2018-01-19T14:22:46.000Z (almost 7 years ago)
• Last Synced: 2023-10-19T22:54:30.087Z (about 1 year ago)
• Topics: paper, zh-cn
• Size: 8.78 MB
• Stars: 2
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Paper-zh

个人所读论文的记录，里面肯定包含错误的理解，欢迎指出，感谢指出。

下述的(*推荐)代表推荐此论文，并不是指写的总结

### 20180102

1. [Learning Deep Features for Discriminative Localization](https://arxiv.org/abs/1512.04150)

2. [Unsupervised Image-to-Image Translation Networks](https://arxiv.org/abs/1703.00848)

### 20180103

1. [Holistically-Nested Edge Detection](https://arxiv.org/abs/1504.06375)

2. [Deeply supervised salient object detection with short connections](https://arxiv.org/abs/1611.04849)

3. [Richer Convolutional Features for Edge Detection](https://arxiv.org/abs/1612.02103)

### 20180104

1. [The Devil is in the Decoder](https://arxiv.org/abs/1707.05847v2) (*推荐)

2. [Instance-Level Salient Object Segmentation](https://arxiv.org/abs/1704.03604)

### 20180105

1. ["Zero-Shot" Super-Resolution using Deep Internal Learning](https://arxiv.org/abs/1712.06087) (*推荐)

2. [Panoptic Segmentation](https://arxiv.org/abs/1801.00868) (*推荐)

### 20180106

1. [Non-Local Deep Features for Salient Object Detection](http://openaccess.thecvf.com/content_cvpr_2017/papers/Luo_Non-Local_Deep_Features_CVPR_2017_paper.pdf)

2. [Learning to Detect Salient Objects with Image-level Supervision](http://openaccess.thecvf.com/content_cvpr_2017/papers/Wang_Learning_to_Detect_CVPR_2017_paper.pdf) (*推荐)

+.+：20180107和20180108打酱油去了....

### 20180109

1. [Fully Convolutional Networks for Semantic Segmentation](https://arxiv.org/abs/1411.4038)

2. [Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs](https://arxiv.org/abs/1412.7062)) (似乎同一篇，但更详细的版本：[DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs](https://arxiv.org/pdf/1606.00915.pdf))

3. [Attention to Scale: Scale-aware Semantic Image Segmentation](https://arxiv.org/abs/1511.03339)

### 20180110

1. [Semantic Image Segmentation via Deep Parsing Network](https://arxiv.org/abs/1509.02634) (*推荐)

2. [Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs](https://arxiv.org/abs/1603.08358)

3. [Deep, Dense, and Low-Rank Gaussian Conditional Random Fields](https://arxiv.org/abs/1611.09051)

### 20180111

1. [Pyramid Scene Parsing Network](https://arxiv.org/abs/1612.01105)

2. [Semantic Segmentation with Reverse Attention](https://arxiv.org/abs/1707.06426) (*推荐)

+.+：201801012和20180113又打酱油去了....（泪崩）

### 20180114

1. [Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach](https://arxiv.org/abs/1703.08448)

2. [Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection](https://arxiv.org/abs/1708.02001)

### 20180116

1. [Dilated Residual Networks](https://arxiv.org/abs/1705.09914) & [Multi-Scale Context Aggregation by Dilated Convolutions](https://arxiv.org/abs/1511.07122)

2. [Learning Affinity via Spatial Propagation Networks](https://arxiv.org/abs/1710.01020) (*推荐)

### 20180117

1. [Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes](https://arxiv.org/abs/1611.08323)

2. [Deep Level Sets for Salient Object Detection](http://openaccess.thecvf.com/content_cvpr_2017/papers/Hu_Deep_Level_Sets_CVPR_2017_paper.pdf)

### 20180118

1. [Not All Pixels Are Equal: Difficulty-aware Semantic Segmentation via Deep Layer Cascade](https://arxiv.org/abs/1704.01344)

### 20190119

1. [Soft Proposal Networks for Weakly Supervised Object Localization](https://arxiv.org/abs/1709.01829)

s