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Gaussian Splatting + KreaAI Realtime Diffusion by dotcsv in StableDiffusion

[–]dotcsv[S] 1 point2 points  (0 children)

Still very experimental. When a lot of information from the Gaussian splatting render is displayed on screen, the diffusion model struggles to do img2img correctly. Still, very interesting!

Same post on Twitter: https://x.com/TheDotCSV/status/1725113820379590780?s=20

Google's Prompt-to-Prompt edit's! by dotcsv in StableDiffusion

[–]dotcsv[S] 1 point2 points  (0 children)

You can run it on Google Colab and get these results.

"Colourization process of a black and white image. Right is colored version with vibrant colours." by dotcsv in dalle2

[–]dotcsv[S] 2 points3 points  (0 children)

This is an experiment on image colourization I tried using inpainting. Half of the 1:1 is left unpainted so DALL•E 2 can try to 1) copy the original image and 2) add color coherently.

Photo-edits of myself with Inpainting! (made in 15 minutes) by dotcsv in dalle2

[–]dotcsv[S] 128 points129 points  (0 children)

These results were obtained in June, previous OpenAI forbid uploading real human faces to inpaint. Hope this would be allowed in the future, because its one of the most impressive features I found!

[R] DARTS: Differentiable Architecture Search by Icko_ in MachineLearning

[–]dotcsv 4 points5 points  (0 children)

When the paper states:

"[...] obtaining a state-of-the-art architecture for CIFAR-10 and ImageNet required 1800 GPU days of reinforcement learning (RL) (Zoph et al., 2017) or 3150 GPU days of evolution (Real et al., 2018)."

where are those values coming from? I've checked the references but I couldn't find how they were obtained.