Venue: ICLR 2018 Workshop

Reviews:

final_score: rating: 7: Good paper, accept
review_content: I like the idea of training a GAN to generate rotated objects. I would not worry too much about the performance since the task itself is very challenging and interesting. This is probably one of the promising ways to connecting 3D geometry with deep learning. And the IterGAN idea is also related to some of the self-supervision works. The paper is well written.
review_title: Good workshop paper

final_score: rating: 7: Good paper, accept
review_content: The paper presents a method for simulate an object rotation by using the generator of a GAN iteratively. I like the idea of using intermediate steps to reach the final degree of rotation and the use of the additional discriminator for that process. The experiments seem adequate and the qualitative results should include an example of all intermediate steps to show how they help the rotation
review_title: Interesting approach for synthesizing object's rotation

Meta-review: Congratulations, your paper was accepted to the ICLR workshop.
Decision: Accept