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pv_word_embedding_pytorch's Introduction

PV_word_embedding_pytorch

多模态特征融合与词嵌入驱动的 三维模型分类检索方法

相关文件下载地址

数据集（datasets）：

pc：pc

view：view

模型（model）：

MVCNN-ALEXNET-save-ckpt.pth：MVCNN-ALEXNET-save-ckpt.pth

GoogleNews-vectors-negative300.bin.gz：GoogleNews-vectors-negative300.bin.gz

PCNet-save-ckpt.pth：PCNet-save-ckpt.pth

PCNet-save-arg.pth：PCNet-save-arg.pth

PVNet2-ALEXNET.pth：PVNet2-ALEXNET.pth

  1. 将数据集下载到本地，并解压到data目录下面

  2. 下载GoogleNews-vectors-negative300.bin.gz预训练模型到根目录

  3. 下载预训练模型MVCNN-ALEXNET-save-ckpt.pth、PCNet-save-ckpt.pth、PCNet-save-arg.pth、PVNet2-ALEXNET.pth

  4. 运行val.py文件，对模型进行评估。

  5. 若要从头训练模型，则分别运行：

    train_mvcnn.py

    train_pc.py

    train.py

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