https://simplestory.github.io/categories/2021/Recent content in 2021 on SimplestoryHugozh-cnSimplestorySat, 07 Aug 2021 00:00:00 +0000https://simplestory.github.io/posts/20210807_1c4ff5cd7d69cb58295eab75872ba2fd/Sat, 07 Aug 2021 00:00:00 +0000https://simplestory.github.io/posts/20210807_1c4ff5cd7d69cb58295eab75872ba2fd/<blockquote> <p>PointNet、PointNet++和Frustum PointNet。常用的3D点云目标检测。</p> </blockquote> <h2 id="pointnet">PointNet</h2> <p>PointNet将深度学习直接应用于点云数据。点云数据是欧式空间下的点的一个子集，有无序性、点与点的空间关系以及不变性这三个性质。</p>https://simplestory.github.io/posts/20210806_8e5f2ccbcaba22801139e42b929ed820/Fri, 06 Aug 2021 00:00:00 +0000https://simplestory.github.io/posts/20210806_8e5f2ccbcaba22801139e42b929ed820/MV3Dhttps://simplestory.github.io/posts/20210805_59094eb979620e0e11f92ffaa71cf228/Thu, 05 Aug 2021 00:00:00 +0000https://simplestory.github.io/posts/20210805_59094eb979620e0e11f92ffaa71cf228/<blockquote> <p>当前工业界常用的多目标跟踪框架。</p> </blockquote> <h2 id="sort">SORT</h2> <p>该算法基于目标检测网络（Faster Rcnn），并利用卡尔曼滤波和匈牙利算法（或KM算法），极大地提高了多目标跟踪的速度。大致流程如下：</p>https://simplestory.github.io/posts/20210804_697dd2d087a31ba4aab4ff575bde80be/Wed, 04 Aug 2021 00:00:00 +0000https://simplestory.github.io/posts/20210804_697dd2d087a31ba4aab4ff575bde80be/动态网络头https://simplestory.github.io/posts/20210803_2d8c6e5a2f995c3808422afc8967c85e/Tue, 03 Aug 2021 00:00:00 +0000https://simplestory.github.io/posts/20210803_2d8c6e5a2f995c3808422afc8967c85e/<blockquote> <p>让它动起来。</p> </blockquote> <h2 id="dynamic-convolution">Dynamic Convolution</h2> <p>一般的静态卷积用同一个卷积核对所有输入图像做相同的操作，而动态卷积会对不同的图像做调整，用更适合的卷积参数进行处理，这样可以在不增加网络深度或宽度的情况下增加模型的表达能力。</p>https://simplestory.github.io/posts/20210516_5df2f4dc23f490c5d68321fa51cabc59/Sun, 16 May 2021 00:00:00 +0000https://simplestory.github.io/posts/20210516_5df2f4dc23f490c5d68321fa51cabc59/条件随机场https://simplestory.github.io/posts/20210430_b30ab79aff271e301dde9ca18c2e8085/Fri, 30 Apr 2021 00:00:00 +0000https://simplestory.github.io/posts/20210430_b30ab79aff271e301dde9ca18c2e8085/<blockquote> <p>图像分割是对图像进行像素级的分类，主要有语义分割(Semantic Segmentation)和实例分割(Instance Segmentation)。语义分割只要求做到像素层面的分割，而实例分割要求在语义分割的基础上实现对不同个体的分割。这篇文章主要简单介绍几种基础的语义分割网络。</p> </blockquote>