论文：Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomo
最近发现了好多基于YOLO修改的网络，一般都是‘剪枝’，已达到轻量级的目的 在目标检测的落地项目中，实时性和精确性的trade-off至关重要，而YOLOv3是目前为止在这方面做得最好的算法。本文通过高斯分布的特性，改进YOLOv3使得网络能够输出每个检测框的不确定性，从而提升了网络的精度。 论文：https://arxiv.org/abs/1904.04620 code
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- 1. Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomo
- 2. [论文解读]Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty
- 3. 【论文阅读】Gaussian YOLOv3
- 4. Gaussian YOLOv3 | ICCV2019，Stronger YOLOv3（有论文翻译）
- 5. 论文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. 新文预览 | IoU-aware Single-stage Object Detector for Accurate Localization
- 8. EAST: An Efficient and Accurate Scene Text Detector——译文
- 9. Bounding Box Regression with Uncertainty for Accurate Object Detection
- 10. Receptive Field Block Net for Accurate and Fast Object Detection论文笔记