Why are people downvoting this? The examples on GitHub are clearly doing the action described (unlike the dachsund above) and don't have the wild deformations that the "Spongebob hugging a cactus" or "Will Smith eating spaghetti" animations have.
Seems fair to choose good results when you try to demonstrate what the software "can" do. Maybe a mention of the process often being iterative would be the most honest, but I think anyone familiar with these tools assume this by now.
To be fair, metrics for vision are limited and many don't know how to correctly inturpret them. You both want to know what's the best images the network can produce a well as the average. Reviewers, unfortunately, just want to reject (no incentive you accept). That said, it can still be a useful tool because you know the best (or near) that the model can produce. This is also why platforms like HuggingFace are so critical.
I do think we should ask more of the research community but just know that this is in fact normal and even standard. Most research judge by things like citations and just reading the works themselves. The more hype in a research area the more noisy the signal for good research. (This is good research imo fwiw)
Can't wait to try it though.