《Unsupervised Learning of Depth and Ego-Motion from Video》論文筆記
Unsupervised Learning of Depth and Ego-Motion from Video 作者：Tinghui Zhou, 項目主頁 摘要 作者針對於無結構化的單目視頻序列的圖像深度獲取提出了一種無監督網絡架構，與之前方法不同在於作者的方法是完全無監督的，而之前的網絡或者需要像素深度的標記，或者需要相機姿勢的標記等。網絡中使用了單目視的深度預測網絡與雙目視的姿勢預測網絡，並
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相關文章
- 1. CVPR 2017【論文筆記】Unsupervised Learning of Depth and Ego-Motion from Video
- 2. Unsupervised Learning of Depth and Ego-Motion from Video論文見解
- 3. 論文筆記-深度估計(6)-Unsupervised Learning of Depth and Ego-Motion from Video
- 4. Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints
- 5. 論文筆記：Unsupervised Learning of Depth and Ego-Motion from Video（無監督深度預測系列4：PoseCNN方法）
- 6. PredNet --- Deep Predictive coding networks for video prediction and unsupervised learning --- 論文筆記
- 7. 論文閱讀： GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose(CVPR2018)
- 8. 【論文筆記】Unsupervised Learning of Video Representations using LSTMs
- 9. 論文筆記（三） 【Learning from Simulated and Unsupervised Images through Adversarial Training】
- 10. 讀論文1-Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric（老師讓看）