001: MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching
Abstract 本文提出的MatchNet包含了（1）從patches中提取特徵的DCNN（深度卷積神經網絡）（2）一個有着三個全連接層的網絡。爲了保證實驗可以復現，本文在標準的數據集上對MatchNet進行訓練。我們將MatchNet拆成feature compution和similarity networks 兩個連續的階段。MatchNet在提升準確性的同時減小了存儲開銷。 1. Intr
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相關文章
- 1. MatchNet: Unifying Feature and Metric Learning for Patch-Based Matching
- 2. 《Learning Semantic Concepts and Order for Image and Sentence Matching》
- 3. Unifying Task-oriented Knowledge Graph Learning and Recommendation
- 4. DIVERSITY REGULARIZED METRIC LEARNING FOR PERSON RE-IDENTIFICATION（ICIP2016）
- 5. Similarity Metric Learning for Face Recognition2013
- 6. Ranked List Loss for Deep Metric Learning
- 7. 2D3D-MatchNet: Learning to Match Keypoints Across 2D Image and 3D Point Cloud
- 8. Matching Networks for one Shot Learning 閱讀筆記
- 9. Survey and experimental study on metric learning methods
- 10. Learning Semantic Concepts and Order for Image and Sentence Matching筆記