Project Statement
One statement: Engineering a Stable-Diffusion model which takes in a text-prompt finds its coherent representations in its latent space and generating videos/GIFs on different machine representation (encoding).
[Results from last model] (Lucidly – Google Drive ).
Descriptive:
My last iterations on this project aimed at generating multiple interpretations off a text prompt and engineering animations between them smoothly compiled as GIFs.
Findings was, human text is often mis-represented in machine’s encoding, therefore, methods like contrastive generation layer needs to be constructed to create a one-many mapping of [human_text] → machine_encodings [0 to n], a walk from 0 → n makes prompts come alive in perspectives. The second half is generating animations like KPMC2 by Katherine Crownson and Stability-AI crew.
After all the machine interrogation, the soundness of generated animations and graphics can only be validate by humans.
Therefore, Algovera like community stands a light where feedback can be crucial.
Deliverables
Research and code helper functions on how to generate coherent text prompts and meaningful visual stories with animation with Lucidly.
Squad
Amit Singh (metamyth)
R&D, Paperplane Technology
Researcher, Active Inference Lab
Twitter: https://twitter.com/not_amyth?t=BSpbbssQAIkrRAgg1ZTUIQ&s=09
Discord: metamyth #8558
USDC Wallet Address: 0x0159af752e0220ed3eef439bef36f982cc0a6fbf