XMem VS latent-diffusion

Compare XMem vs latent-diffusion and see what are their differences.


[ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model (by hkchengrex)


High-Resolution Image Synthesis with Latent Diffusion Models (by CompVis)
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XMem latent-diffusion
11 70
1,534 9,827
- 3.4%
6.6 0.0
6 days ago 3 months ago
Python Jupyter Notebook
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.


Posts with mentions or reviews of XMem. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-11.


Posts with mentions or reviews of latent-diffusion. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-21.

What are some alternatives?

When comparing XMem and latent-diffusion you can also consider the following projects:


dalle-mini - DALLĀ·E Mini - Generate images from a text prompt


hent-AI - Automation of censor bar detection


DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch

stable-diffusion - A latent text-to-image diffusion model

VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.

CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

tortoise-tts - A multi-voice TTS system trained with an emphasis on quality

glid-3-xl - 1.4B latent diffusion model fine tuning

big-sleep - A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun