HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection
文章地址：點擊打開鏈接 本文是region-based object detection framework。相比與faster rcnn，hypernet更擅長處理小物體，並且產生更高質量的proposal。 整體的框架見下圖： Network for Hyper Feature Extraction: RCNN之後的framework在做小物體檢測時有一個通病，就是物體的的信息會損失的非常厲害
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相關文章
- 1. HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detection
- 2. Joint 3D Proposal Generation and Object Detection from View Aggregation論文學習
- 3. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- 4. 【Faster RCNN】《Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks》
- 5. Region-Based Convolutional Networks for Accurate Object Detection and Segmentation
- 6. HyperNet, RON, FPN
- 7. （動工中）論文梳理 —— Joint 3D Proposal Generation and Object Detection from View Aggregation
- 8. 論文筆記：Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- 9. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks論文筆記
- 10. (41)[NIPS15] Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks