Few-Example Object Detection with Model Communication 思想
沒有多模型學習的框架 使用一個模型，進行 self-paced learning 存在問題：僅使用很少的標註數據，可能會陷入局部最小狀態。（Local minimum.） 作者提出的模型如下圖 箭頭代表生成的僞標籤 流向方向，3個模型是不一樣的 （交流可以體現爲 數據的交流）
相關文章
- 1. 論文閱讀筆記《Few-Example Object Detection with Model Communication》
- 2. [Arxiv1706] Few-Example Object Detection with Model Communication 論文筆記
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相關文章
- 1. 論文閱讀筆記《Few-Example Object Detection with Model Communication》
- 2. [Arxiv1706] Few-Example Object Detection with Model Communication 論文筆記
- 3. MyDLNote-Detection: DETR : End-to-End Object Detection with Transformers
- 4. End-to-End Object Detection with Transformers
- 5. DenseBox: Unifying Landmark Localization with End to End Object Detection
- 6. One-shot object detection
- 7. TensorFlow Object Detection API
- 8. Object detection
- 9. Deep Saliency:Multi_Task Deep Neural Network Model for Salient object detection
- 10. Soft-NMS: Improving object detection with one line of code