Real-Time monocular depth estimation using synthetic data with domain adaptation via IST
4 Contributions: synthetic depth prediction - a directly supervised model using a light-weight architecture with skip connections that can predict depth based on high-quality synthetic depth training
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- 1. 11.Unsupervised Monocular Depth Estimation with Left-Right Consistency
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- 3. Domain Adaptation via Transfer Component Analysis
- 4. 【論文閱讀筆記】High Quality Monocular Depth Estimation via Transfer Learning
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- 6. [MICCAI2019]Unsupervised Domain Adaptation via Disentangled Representations
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相關文章
- 1. 11.Unsupervised Monocular Depth Estimation with Left-Right Consistency
- 2. Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation
- 3. Domain Adaptation via Transfer Component Analysis
- 4. 【論文閱讀筆記】High Quality Monocular Depth Estimation via Transfer Learning
- 5. Unsupervised Monocular Depth Estimation With Left-Right Consistency 論文筆記
- 6. [MICCAI2019]Unsupervised Domain Adaptation via Disentangled Representations
- 7. AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation
- 8. Synthetic to real adaptation with generative correlation alignment network
- 9. [Synthetic-data-with-text-and-image]
- 10. CVPR2017 Oral【論文筆記】Unsupervised Monocular Depth Estimation with Left-Right Consistency