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Anchor-free Detection专题
Lejian Ren
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为什么要有anchor 直接预测坐标难以训练 F(x) =(x1, y1, x2, y2)
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早期的anchor-free: DenseBox
FCN形式，输出5通道（score + 4个坐标变换） 对物体size差距较大的图像效果不好（FPN?） Huang, Lichao, et al. "Densebox: Unifying landmark localization with end to end object detection." arXiv preprint arXiv: (2015).
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Denet 预测每个像素是什么类型的corner DeNet
Tychsen-Smith, Lachlan, and Lars Petersson. "Denet: Scalable real-time object detection with directed sparse sampling." Proceedings of the IEEE International Conference on Computer Vision
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CornerNet Law, Hei, and Jia Deng. "Cornernet: Detecting objects as paired keypoints." Proceedings of the European Conference on Computer Vision (ECCV)
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CornerNet 为什么不用anchor 为什么用corner anchor多 超参多 Center比较难定位，需要考虑和四个边的关系
Law, Hei, and Jia Deng. "Cornernet: Detecting objects as paired keypoints." Proceedings of the European Conference on Computer Vision (ECCV)
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CornerNet Heatmap参考了key point Embedded是一个d-1的数
Offset用来减小从feature map到原图的影响（共享） Law, Hei, and Jia Deng. "Cornernet: Detecting objects as paired keypoints." Proceedings of the European Conference on Computer Vision (ECCV)
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CornerNet 预测corner 高斯 Focal loss
Law, Hei, and Jia Deng. "Cornernet: Detecting objects as paired keypoints." Proceedings of the European Conference on Computer Vision (ECCV)
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CornerNet Corner pooling 为什么需要：物体的corner往往不在物体里面
Law, Hei, and Jia Deng. "Cornernet: Detecting objects as paired keypoints." Proceedings of the European Conference on Computer Vision (ECCV)
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CornerNet Grouping Corner
Law, Hei, and Jia Deng. "Cornernet: Detecting objects as paired keypoints." Proceedings of the European Conference on Computer Vision (ECCV)
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CornerNet Law, Hei, and Jia Deng. "Cornernet: Detecting objects as paired keypoints." Proceedings of the European Conference on Computer Vision (ECCV)
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CornerNet Law, Hei, and Jia Deng. "Cornernet: Detecting objects as paired keypoints." Proceedings of the European Conference on Computer Vision (ECCV)
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CornerNet-Lite 加速 CornerNet-Saccade CornerNet-Squeeze 减小输入尺寸
利用attention减少需要预测的点 CornerNet-Squeeze 修改backbone Law, Hei, et al. "CornerNet-Lite: Efficient Keypoint Based Object Detection." arXiv preprint arXiv: (2019).
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CornerNet-Lite CornerNet-Saccade
Law, Hei, et al. "CornerNet-Lite: Efficient Keypoint Based Object Detection." arXiv preprint arXiv: (2019).
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CornerNet-Lite Law, Hei, et al. "CornerNet-Lite: Efficient Keypoint Based Object Detection." arXiv preprint arXiv: (2019).
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CenterNet-1 预测key point 预测长宽
X. Zhou, D. Wang, and P. Krähenbühl, “Objects as Points,” 2019.
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CenterNet-1 Loss functions
X. Zhou, D. Wang, and P. Krähenbühl, “Objects as Points,” 2019.
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CenterNet-1 X. Zhou, D. Wang, and P. Krähenbühl, “Objects as Points,” 2019.
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CenterNet-2 CenterNet的缺点 从预测corner变成预测corner+center
原文认为：只预测corner无法很好的catch物体本身的信息 我认为：embedding没有区分度 从预测corner变成预测corner+center 只有预测的center在预测的corner内部，才是正确的预测 Duan, Kaiwen, et al. "CenterNet: Keypoint Triplets for Object Detection." arXiv preprint arXiv: (2019).
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CenterNet-2 Duan, Kaiwen, et al. "CenterNet: Keypoint Triplets for Object Detection." arXiv preprint arXiv: (2019).
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CenterNet-2 如何判断center在corner内部（判定区域的设定） 太大，precision低 太小，recall低 自适应
Duan, Kaiwen, et al. "CenterNet: Keypoint Triplets for Object Detection." arXiv preprint arXiv: (2019).
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CenterNet-2 Center pooling Cascade corner pooling
Duan, Kaiwen, et al. "CenterNet: Keypoint Triplets for Object Detection." arXiv preprint arXiv: (2019).
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CenterNet-2 Duan, Kaiwen, et al. "CenterNet: Keypoint Triplets for Object Detection." arXiv preprint arXiv: (2019).
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RepPoints（representative points）
motivation： 物体空间形状的可以通过几个reppoints来表示，通过学多个reppoints， 就可以用其外接矩形来表示物体的框 Z. Yang, S. Liu, H. Hu, L. Wang, and S. Lin, “RepPoints: Point Set Representation for Object Detection,” 2019.
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RepPoints 和deformable convolution 完美结合
Z. Yang, S. Liu, H. Hu, L. Wang, and S. Lin, “RepPoints: Point Set Representation for Object Detection,” 2019.
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RepPoints Pipeline： Learning RepPoints RepPoints refinement
Converting RepPoints to bounding box Min-max function Partial min-max function Moment-based function (reppoints均值和二阶矩) Z. Yang, S. Liu, H. Hu, L. Wang, and S. Lin, “RepPoints: Point Set Representation for Object Detection,” 2019.
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RepPoints Z. Yang, S. Liu, H. Hu, L. Wang, and S. Lin, “RepPoints: Point Set Representation for Object Detection,” 2019.
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RepPoints Z. Yang, S. Liu, H. Hu, L. Wang, and S. Lin, “RepPoints: Point Set Representation for Object Detection,” 2019.
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一点看法 为什么object detection没有一开始就anchor-free？
目前的anchor-free就是“anchor-free”吗？ Anchor-free可能的发展方向
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