圖像分割"LIP: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing"
數據集：http://hcp.sysu.edu.cn/lip code: https://github.com/Engineering-Course/LIP_SSL. 做人體部件分割，構建了一個新的數據庫「LIP」，包含19個語義標記。在訓練中融入結構信息，提升分割效果。 人體分割具體應用：行人再認證，行爲分析等。 目前三個人體部件數據庫ATR,Pascal-Person-Part和LIP複雜度比
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相關文章
- 1. 論文閱讀：《LIP: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing》
- 2. 多人部件解析--Towards Real World Human Parsing: Multiple-Human Parsing in the Wild
- 3. Human Semantic Parsing for Person Re-identification(Parsing 方法)
- 4. [paper] Multiple Human Parsing
- 5. Macro-Micro Adversarial Network for Human Parsing
- 6. human parsing—學習筆記
- 7. Human Semantic Parsing for Person Re-identification
- 8. CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmark 論文閱讀
- 9. Vision-Based Parking-Slot Detection: A Benchmark and A Learning-Based Approach
- 10. Deep Learning based Recommender System: A Survey and New Perspectives