Pytorch code for OVPT [ACCV 2022(Oral)]

OVPT: Optimal Viewset Pooling Transformer for 3D Object Recognition

Requirement

This code is tested on Python 3.6 and Pytorch 1.6.0

Dataset

First download the 20 views ModelNet10 and ModelNet40 dataset provided by [rotationnet] and put it under data

https://data.airc.aist.go.jp/kanezaki.asako/data/modelnet10v2png_ori2.tar https://data.airc.aist.go.jp/kanezaki.asako/data/modelnet40v2png_ori4.tar

Then python ov.py to construct the optimal viewset

Train ande test:

python train.py

Reference

Su, H., Maji, S., Kalogerakis, E., Learned-Miller, E.: Multi-view convolutional neural networks for 3d shape recognition. In: 2015 IEEE International Conference on Computer Vision (ICCV). (2015) 945–953

Kanezaki, A., Matsushita, Y., Nishida, Y.: Rotationnet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. (2018) 5010–5019