StyleCLIP VS alias-free-gan

While CLIP on its own is useful for applications such as zero-shot classification, semantic searches, and unsupervised data exploration, CLIP is also used as a building block in a vast array of multimodal applications, from Stable Diffusion and DALL-E to StyleCLIP and OWL-ViT. For most of these downstream applications, the initial CLIP model is regarded as a “pre-trained” starting point, and the entire model is fine-tuned for its new use case.

I'm currently building a fork for StyleCLIP global directions which allows you to control multiple semantic parameters simoultaneously to generate and edit an image with StyleGAN and CLIP in realtime. I want to showcase its potential as a design tool. Unfortunately, GAN weights are trained on very domain-specific (faces, cars, churches) data. This makes them inferior to modern diffusion models which I can use to generate whatever comes to mind. Although I know we won't have a GAN-based DALL-E counterpart anytime soon, I still would love to use my system with weights that can output a wide variety of things.

(Added Feb. 15, 2021) StyleCLIP - Colaboratory by orpatashnik. Uses StyleGAN to generate images. GitHub. Twitter reference. Reddit post.

I used StyleCLIP. I purchased some Google Colab time to use their GPUs. I'll probably do some more later this week.

Link for Styleclip

So, I watched this Corridor Crew video on generating realistic faces from CG characters, and I wanted to try it out on the RDR2 models. The github link for the original work is here. If you guys are interested I can generate the faces of more characters from RDR2 and RDR1. I can even try some from RD Revolver.

Combining these methods with CLIP allows you to generate images based on text. This one uses a face generator. https://github.com/orpatashnik/StyleCLIP

Curious how you managed to make this since the code hasn't been released yet https://github.com/NVlabs/alias-free-gan Did you write it from the research paper, if so do you have a github link?

This isn't true. I do ML every day. You are mistaken.

I click the website. I search "model". I see two results. Oh no, that means no download link to model.

I go to the github. Maybe model download link is there. I see zero code: https://github.com/NVlabs/alias-free-gan

zero code. Zero model.

You, and everyone like you, who are gushing with praise and hypnotized by pretty images and a nice-looking pdf, are doing damage by saying that this is correct and normal.

The thing that's useful to me, first and foremost, is a model. Code alone isn't useful.

Code, however, is the recipe to create the model. It might take 400 hours on a V100, and it might not actually result in the model being created, but it slightly helps me.

There is no code here.

Do you think that the pdf is helpful? Yeah, maybe. But I'm starting to suspect that the pdf is in fact a tech demo for nVidia, not a scientific contribution whose purpose is to be helpful to people like me.

Okay? Model first. Code second. Paper third.

Every time a tech demo like this comes out, I'd like you to check that those things exist, in that order. If it doesn't, it's not reproducible science. It's a tech demo.

I need to write something about this somewhere, because a large number of people seem to be caught in this spell. You're definitely not alone, and I'm sorry for sounding like I was singling you out. I just loaded up the comment section, saw your comment, thought "Oh, awesome!" clicked through, and went "Oh no..."