Controllable Image Generation
Free controllable image generation AI tools for creating customizable visuals, helping artists and designers produce tailored images for projects.
AmbiGen can generate ambigrams by optimizing letter shapes for clear reading from two angles. It improves word accuracy by over 11.6% and reduces edit distance by 41.9% on the 500 most common English words.
It’s been a while since I last doomed the TikTok dancers. MagicDance is gonna doom them some more. This model can combine human motion with reference images to precisely generate appearance-consistent videos. While the results still contain visible artifacts and jittering, give it a few months and I’m sure we can’t tell the difference no more.
Break-A-Scene can extract multiple concepts from a single image using segmentation masks. It allows users to re-synthesize individual concepts or combinations in different contexts, enhancing scene generation with a two-phase customization process.
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MultiDiffusion can generate high-quality images using a pre-trained text-to-image diffusion model. It allows users to control aspects like image size and includes features for guiding images with segmentation masks and bounding boxes.
ControlNet can add control to text-to-image diffusion models. It lets users manipulate image generation using methods like edge detection and depth maps, while working well with both small and large datasets.
StyleGAN-T can generate high-quality images at 512x512 resolution in just 2 seconds using a single NVIDIA A100 GPU. It solves problems in text-to-image synthesis, like stable training on diverse datasets and strong text alignment.