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:  We train the network on six object categories with 149 objects and 100K rendered images, achieving an accuracy of 82.5\% on novel object instances in trained categories. Experiments also show how this method enables generalization to novel categories and be applied to real-world images without fine-tuning.