Stacked_DMSHN_bokeh
Official Repository for our CVPRW (MAI'21) paper. (by saikatdutta)
stargan-v2
StarGAN v2 - Official PyTorch Implementation (CVPR 2020) (by clovaai)
Stacked_DMSHN_bokeh | stargan-v2 | |
---|---|---|
1 | 1 | |
20 | 3,418 | |
- | 0.2% | |
1.8 | 0.0 | |
over 2 years ago | about 1 year ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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.
Stacked_DMSHN_bokeh
Posts with mentions or reviews of Stacked_DMSHN_bokeh.
We have used some of these posts to build our list of alternatives
and similar projects.
-
CVPRW paper on Monocular Bokeh Effect Rendering
Code: https://github.com/saikatdutta/Stacked_DMSHN_bokeh
stargan-v2
Posts with mentions or reviews of stargan-v2.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-07-20.
-
How to Run stargan2 on Google Colab
This version of StarGAN2 (coined as 'Post-modern Style Transfer') is intended mostly for fellow artists, who rarely look at scientific metrics, but rather need a working creative tool. At least, this is what I use nearly daily myself. Here are few pieces, made with it: Terminal Blink, Occurro, etc. Tested on Pytorch 1.4-1.8. Sequence-to-video conversions require FFMPEG. For more explicit details refer to the original implementation.
What are some alternatives?
When comparing Stacked_DMSHN_bokeh and stargan-v2 you can also consider the following projects:
style-aware-discriminator - CVPR 2022 - Official PyTorch implementation of "A Style-Aware Discriminator for Controllable Image Translation"
AvatarMe - Public repository for the CVPR 2020 paper AvatarMe and the TPAMI 2021 AvatarMe++
ALAE - [CVPR2020] Adversarial Latent Autoencoders
stargan2 - StarGAN2 for practice
VIBE - Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"
meshed-memory-transformer - Meshed-Memory Transformer for Image Captioning. CVPR 2020