论文阅读：Multi-view Convolutional Neural Networks for 3D Shape Recognition

时间 2019-12-05

标签论文阅读 multi view convolutional neural networks 3d shape recognition 繁體版

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Preface 今天阅读一篇ICCV2015的论文：《Multi-view Convolutional Neural Networks for 3D Shape Recognition》，简称：MVCNN。这里是Paper Homepage 这里是Paper Codegit 这篇文章的创新点在于：用物体的三维数据从不一样“视角”所获得的二维渲染图，做为原始的训练数据。用经典、成熟的二维图像卷积

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1. 论文阅读：Multi-view Convolutional Neural Networks for 3D Shape Recognition
2. 【论文精读】Multi-view Convolutional Neural Networks for 3D Shape Recognition
3. GVCNN: Group-View Convolutional Neural Networks for 3D Shape Recognition
4. MVCNN:Multi-view Convolutional Neural Networks for 3D Shape Recognition
5. ICCV2015_Multi-view Convolutional Neural Networks for 3D Shape Recognition
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7. 《3D Convolutional Neural Networks for Human Action Recognition》论文阅读笔记
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9. 论文阅读-Fast Algorithms for Convolutional Neural Networks
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1. 论文阅读：Multi-view Convolutional Neural Networks for 3D Shape Recognition
2. 【论文精读】Multi-view Convolutional Neural Networks for 3D Shape Recognition
3. GVCNN: Group-View Convolutional Neural Networks for 3D Shape Recognition
4. MVCNN:Multi-view Convolutional Neural Networks for 3D Shape Recognition
5. ICCV2015_Multi-view Convolutional Neural Networks for 3D Shape Recognition
6. 论文：3D Convolutional Neural Networks for Human Action Recognition
7. 《3D Convolutional Neural Networks for Human Action Recognition》论文阅读笔记
8. 论文阅读：《Convolutional Neural Networks for Sentence Classification》
9. 论文阅读-Fast Algorithms for Convolutional Neural Networks
10. Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition论文阅读翻译

>>更多相关文章<<