We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
Great work guys.
I was able to run the code on CUB dataset. But when I tried to run training_test_shape_net.py on Shape Net v2 chair class I'm getting errors because of missing files, unmatched file names, etc.
So it would be helpful if you provide Shapenet Dataset Folder structure and files(images, masks) description or a sample folder and clear instructions for training the model shapenet dataset.
And also if possible give pre-trained weights for the Shape net dataset models
Great work guys. I was able to run the code on CUB dataset. But when I tried to run
training_test_shape_net.pyon Shape Net v2 chair class I'm getting errors because of missing files, unmatched file names, etc.So it would be helpful if you provide Shapenet Dataset Folder structure and files(images, masks) description or a sample folder and clear instructions for training the model shapenet dataset. And also if possible give pre-trained weights for the Shape net dataset models
Thank you