EMR: To Learn or Not to Learn: Visual Localization from Essential Matrices && 2020論文筆記
通訊作者： Laura Leal-Taix ́e 第一作者：Qunjie Zhou 研究機構：慕尼黑工業大學,查爾默斯理工大學,微軟 EMR證明了估計本質矩陣是比直接預測場景座標更好的選擇。理論上來說，相對位姿迴歸相比於絕對位姿迴歸應當有更好的跨場景泛化性，但是實驗結果證明並非如此。作者通過實驗探究發現，基於深度學習的場景座標迴歸方法之所以泛化性差是因爲位姿迴歸層輸入的的高層級特徵損失了定位精度，
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相關文章
- 1. 【論文筆記】To Learn or Not to Learn: Visual Localization from Essential Matrices（ICRA 2020）
- 2. 論文筆記——Comparing to Learn
- 3. ATTENTION, LEARN TO SOLVE ROUTING PROBLEMS!論文筆記
- 4. Zoom to Learn, Learn to Zoom
- 5. Learning how to learn
- 6. 【超分辨率】Zoom to Learn, Learn to Zoom
- 7. Learning to Learn
- 8. 11 Essential Skills to become Software Developer in 2020
- 9. 論文筆記：Learning how to Active Learn: A Deep Reinforcement Learning Approach
- 10. Learn How to Perform Feature Extraction from Graphs using DeepWalk