論文：Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomo
最近發現了好多基於YOLO修改的網絡，一般都是‘剪枝’，已達到輕量級的目的 在目標檢測的落地項目中，實時性和精確性的trade-off至關重要，而YOLOv3是目前爲止在這方面做得最好的算法。本文通過高斯分佈的特性，改進YOLOv3使得網絡能夠輸出每個檢測框的不確定性，從而提升了網絡的精度。 論文：https://arxiv.org/abs/1904.04620 code
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相關文章
- 1. Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomo
- 2. [論文解讀]Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty
- 3. 【論文閱讀】Gaussian YOLOv3
- 4. Gaussian YOLOv3 | ICCV2019，Stronger YOLOv3（有論文翻譯）
- 5. 論文SDP + RCNN | Exploit All the Layers: Fast and Accurate CNN Object Detector with SDP and CRC
- 6. An Efficient and Accurate Scene Text Detector
- 7. 新文預覽 | IoU-aware Single-stage Object Detector for Accurate Localization
- 8. EAST: An Efficient and Accurate Scene Text Detector——譯文
- 9. Bounding Box Regression with Uncertainty for Accurate Object Detection
- 10. Receptive Field Block Net for Accurate and Fast Object Detection論文筆記