weakness of the paper are as follows (from my perspective): * (strength) the authors introduce a generative approach for applying Hindsight Experience Replay (HER) in visual domains: the idea is simple and has the potential to improve our current Deep RL methods. * (weakness) currently, the paper does not seem to have a detailed discussion on how their generative model was trained to produce images containing the goal information. The authors do clarify this on their feedback and it would be useful if they also add this discussion on their next version of the paper. More importantly, including this discussion is useful for the Deep RL community. * (weakness) their current approach of training the generative model relies on manually annotating the goal images, which may prevent scalability of the algorithm. Addressing this could make their approach be more impactful.
* (strength) the authors introduce a generative approach for applying Hindsight Experience Replay (HER) in visual domains: the idea is simple and has the potential to improve our current Deep RL methods.