Domain adaptive faster-rcnn for object detection in the wild 論文筆記
2018年CVPR文章，基於Faster-RCNN，進行領域自適應改進（似遷移學習），用在進行霧氣，光線不良狀況下的野外遷移探測活動（複雜多變的場景）git 解決domain shift 1.image level :scale,style,illumination 2.instance level:obj appearance ,size and orientationgithub 主要貢獻 1
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相關文章
- 1. Domain adaptive faster-rcnn for object detection in the wild 論文筆記
- 2. 論文筆記：Domain Adaptive Faster R-CNN for Object Detection in the Wild
- 3. 論文筆記：Large-Scale Object Detection in the Wild from Imbalanced Multi-Labels
- 4. Exploring Categorical Regularization for Domain Adaptive Object Detection
- 5. 論文筆記：Strong-Weak Distribution Alignment for Adaptive Object Detection
- 6. Traffic-Sign Detection and Classification in the Wild 論文筆記
- 7. 【論文筆記】Learning from Synthetic Data for Crowd Counting in the Wild
- 8. Material Recognition in the Wild with the Materials in Context Database論文筆記
- 9. Choosing Smartly: Adaptive Multimodal Fusion for Object Detection in Changing Environments論文閱讀筆記
- 10. 論文見解之SRN: Side-output Residual Network for Object Symmetry Detection in the Wild