zlacker

[return to "Imagen, a text-to-image diffusion model"]
1. benwik+L6[view] [source] 2022-05-23 21:29:19
>>kevema+(OP)
Would be fascinated to see the DALL-E output for the same prompts as the ones used in this paper. If you've got DALL-E access and can try a few, please put links as replies!
◧◩
2. joeyco+Pf[view] [source] 2022-05-23 22:19:12
>>benwik+L6
Posting a few comparisons here.

https://twitter.com/joeyliaw/status/1528856081476116480?s=21...

◧◩◪
3. dclowd+b41[view] [source] 2022-05-24 06:26:15
>>joeyco+Pf
Looking at these… I can’t help but wonder if these are literal examples of AI imagination?
◧◩◪◨
4. joeyco+z41[view] [source] 2022-05-24 06:29:58
>>dclowd+b41
I've started to ask myself if my own creativity is a result of random sampling from the diffusion tapestry of associated memories and experience on that topic.
◧◩◪◨⬒
5. Nition+Bj1[view] [source] 2022-05-24 08:52:48
>>joeyco+z41
I do wonder what Dall-E 2 would output for a request along the lines of "A still life of a vase of flowers in a completely new art style."
◧◩◪◨⬒⬓
6. zimpen+7q1[view] [source] 2022-05-24 09:55:20
>>Nition+Bj1
Don't have access to Dall-E 2 or Imagen but I do have [1] and [2] locally and they produced [3] with that prompt.

[1] https://github.com/nerdyrodent/VQGAN-CLIP.git [2] https://github.com/CompVis/latent-diffusion.git [3] https://imgur.com/a/dCPt35K

◧◩◪◨⬒⬓⬔
7. Nition+Jj3[view] [source] 2022-05-24 20:40:31
>>zimpen+7q1
Nice. Latent-diffusion has come out very traditional but the VQGAN/CLIP ones are fairly original.
[go to top]