Before revision:  We train the network on six object categories with 149 objects and 100K rendered images, achieving an accuracy of 82.5\% . Experiments show our method generalizes to novel object categories in simulation and can be applied to real-world images without fine-tuning.
After revision:  The network achieves an articulation type classification accuracy of 82.5\% . Experiments show our method generalizes to novel object categories in simulation and can be applied to real-world images without fine-tuning.