caiyu97 / MVCNN

Multi-view dual attention network for 3D object recognition (Neural Computing and Applications, 2021）

PyTorch code for MVDAN

A Pytorch implementation of Multi-view Dual Attention Network for 3D Object Recognitionn (MVDAN)

In this paper, the 3D object recognition problem is converted to multi-view 2D image classification problem. For each 3D object, there are multiple images taken from different views

Dependecies

• Python 3.6
• PyTorch 1.2.0
• numpy

Dataset

• ModelNet CAD data can be found at Princeton
• ModelNet40 12-view png images can be downloaded at modelnet40_images_new_12x (1.6GB)
• You can also create 3-view png images and 6-view png images by reducing the number of 12 views

Train the model

python train.py -name MVDAN -num_models 1000 -weight_decay 0.0001 -num_views 12 -cnn_name resnet50