Image AI Tools

FreCaS can generate high-resolution images quickly using a method that breaks the process into stages with increasing detail. It is about 2.86× to 6.07× faster than other tools for creating 2048×2048 images and improves image quality significantly.

Stable-Hair can robustly transfer a diverse range of real-world hairstyles onto user-provided faces for virtual hair try-on. It employs a two-stage pipeline that includes a Bald Converter for hair removal and specialized modules for high-fidelity hairstyle transfer.

MagicTailor can reuse specific parts of images in text-to-image diffusion models. It improves image quality and keeps the subject’s identity clear while reducing semantic pollution.

DisEnvisioner can generate customized images from a single visual prompt and extra text instructions. It filters out irrelevant details and provides better image quality and speed without needing extra tuning.

UniPortrait can customize images of one or more people with high quality. It allows for detailed face editing and uses free-form text descriptions to guide changes.

HART is an autoregressive transformer model that can generate high-quality 1024x1024 images from text 3x times faster than SD3-Medium.

EfficientViT can speed up high-resolution diffusion models by compressing data with a ratio of up to 128 while keeping good image quality. It achieves a 19.1x speed increase for inference and a 17.9x speed increase for training on ImageNet 512x512 compared to other autoencoders.

CtrLoRA can adapt a base ControlNet for image generation with just 1,000 data pairs in under one hour of training on a single GPU. It reduces learnable parameters by 90%, making it much easier to create new guidance conditions.

TweedieMix can generate images and videos that combine multiple personalized concepts.

RFNet is a training-free approach that bring better prompt understanding to image generation. Adding support for prompt reasoning, conceptual and metaphorical thinking, imaginative scenarios and more.

SEMat can improve interactive image matting! It enhances network design and training to achieve better transparency, detail, and accuracy than methods like MAM and SmartMat.

OmniBooth can generate images with precise control over their layout and style. It allows users to customize images using masks and text or image guidance, making the process flexible and personal.

Love this one! SVGCustomization is a novel pipeline that is able to edit existing vector images with text prompts while preserving the properties and layer information vector images are made of.

MambaPainter can turn images into an oil painting style by predicting over 100 brush strokes in one step.

ProCreate boosts the diversity and creativity of diffusion-based image generation while avoiding the replication of training data. By pushing generated image embeddings away from reference images, it improves the quality of samples and lowers the risk of copying copyrighted content.

Prompt Sliders can control and edit concepts in diffusion models. It allows users to adjust the strength of concepts with just 3KB of storage per embedding, making it much faster than traditional LoRA methods.

StoryMaker can generate a series of images with consistent characters across multiple images. It keeps the same facial features, clothing, hairstyles, and body types, allowing for cohesive storytelling.

InstantDrag can edit images quickly using drag instructions without needing masks or text prompts. It learns motion dynamics with a two-network system, allowing for real-time, photo-realistic editing.

Exploiting Diffusion Prior for Real-World Image Super-Resolution can restore high-quality images from low-resolution inputs using pre-trained text-to-image diffusion models. It allows users to balance image quality and fidelity through a controllable feature wrapping module and adapts to different image resolutions with a progressive aggregation sampling strategy.

MagicMan can generate high-quality 3D images and normal maps of humans from a single photo.