CLIP-Style-Transfer
Doing style transfer with linguistic features using OpenAI's CLIP. (by Zasder3)
TediGAN
[CVPR 2021] Pytorch implementation for TediGAN: Text-Guided Diverse Face Image Generation and Manipulation (by IIGROUP)
| CLIP-Style-Transfer | TediGAN | |
|---|---|---|
| 2 | 1 | |
| 13 | 361 | |
| - | 0.0% | |
| 0.0 | 0.0 | |
| almost 3 years ago | about 1 year ago | |
| Jupyter Notebook | Python | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
CLIP-Style-Transfer
Posts with mentions or reviews of CLIP-Style-Transfer.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-03.
-
test
(Added Mar. 8, 2021) CLIP Style Transfer Test.ipynb - Colaboratory by Zasder3. Uses VGG19's conv4_1 to generate images. GitHub. Twitter reference.
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[Project] Learning Artistic Style From Language Features using CLIP
Code: https://github.com/Zasder3/CLIP-Style-Transfer
TediGAN
Posts with mentions or reviews of TediGAN.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-03.
-
test
(Added Feb. 23, 2021) TediGAN - Colaboratory by weihaox. Uses StyleGAN to generate images. GitHub. I got error "No pre-trained weights found for perceptual model!" when I used the Colab notebook, which was fixed when I made the change mentioned here. After this change, I still got an error in the cell that displays the images, but the results were in the remote file system. Use the "Files" icon on the left to browse the remote file system.
What are some alternatives?
When comparing CLIP-Style-Transfer and TediGAN you can also consider the following projects:
Colab-deep-daze - Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
StyleCLIP - Using CLIP and StyleGAN to generate faces from prompts.
StyleCLIP - Official Implementation for "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery" (ICCV 2021 Oral)
VectorAscent - Generate vector graphics from a textual caption
AuViMi - AuViMi stands for audio-visual mirror. The idea is to have CLIP generate its interpretation of what your webcam sees, combined with the words thare are spoken.
clipping-CLIP-to-GAN
Story2Hallucination
aphantasia - CLIP + FFT/DWT/RGB = text to image/video
CLIP-Style-Transfer vs Colab-deep-daze
TediGAN vs StyleCLIP
CLIP-Style-Transfer vs StyleCLIP
TediGAN vs Colab-deep-daze
CLIP-Style-Transfer vs StyleCLIP
TediGAN vs VectorAscent
CLIP-Style-Transfer vs AuViMi
TediGAN vs AuViMi
CLIP-Style-Transfer vs clipping-CLIP-to-GAN
TediGAN vs Story2Hallucination
CLIP-Style-Transfer vs aphantasia
TediGAN vs clipping-CLIP-to-GAN