FLUX.1-dev-Controlnet-Inpainting-Beta is an image restoration model developed by Alibaba's creative team, featuring significant improvements in image restoration. It supports direct processing and generation at 1024x1024 resolution without the need for additional upscaling, providing higher quality and more detailed outputs. The model has been fine-tuned to capture and reproduce more details in the restoration areas, with enhanced prompt explanations that allow for more precise control over the generated content.

FLUX-Controlnet-Inpainting is an image restoration tool released by the Alibaba Mama Creative Team, based on the FLUX.1-dev model. This tool utilizes deep learning technology to restore images, filling in missing sections and suitable for image editing and enhancement. It performs best at a resolution of 768x768, providing high-quality image restoration results. Currently, the tool is in the alpha testing phase, with future updates planned.

AuraSR-v2 is a GAN-based image super-resolution model designed for enlarging generated images, and it is a variant of the GigaGAN paper. The PyTorch implementation of this model is based on the unofficial lucidrains/gigagan-pytorch repository. It significantly enhances the resolution of images while preserving their quality, which is particularly important for applications requiring high-definition image outputs.

LighTDiff is a deep learning model designed to enhance surgical endoscope images under low-light conditions. Utilizing T-Diffusion technology, the model effectively increases the brightness and clarity of images, significantly contributing to surgical safety and efficiency. This technology has been accepted for early publication at the MICCAI2024 conference, and the code is open-source, available for research and practical applications.

ComfyUI-SuperBeasts is an image processing application designed to enhance the dynamic range and visual appeal of images. It offers a set of adjustable parameters for finetuning HDR effects according to user preferences. The application features: * Adjust the intensity of shadows, highlights, and overall HDR effect; * Apply gamma correction to control overall brightness and contrast; * Enhance contrast and color saturation for more vibrant results; * Preserve color accuracy by processing images in the LAB color space; * Utilize brightness-based masks for targeted adjustments; * Blend adjusted luminosity with the original luminosity to achieve a balanced effect.

OMG (Once More Generalization) is an open-source image super-resolution tool that utilizes deep learning techniques to enhance image resolution. The project aims to improve image quality by using AI models, ensuring sharpness and detail even after enlargement.

Diffuse to Choose is a diffusion-based image repair model primarily designed for virtual try-on scenarios. It can preserve the details of the reference item while repairing the image and perform accurate semantic operations. By directly integrating the detail feature of the reference image into the latent feature map of the main diffusion model and combining it with perceptual loss to further preserve the details of the reference item, the model achieves a good balance between fast inference and high-fidelity details.

Denoising Vision Transformers (DVT) is a novel noise model for Vision Transformers (ViTs). By dissecting the ViT output and introducing a learnable denoiser, DVT can extract noise-free features, significantly improving the performance of Transformer-based models in both offline and online applications. DVT does not require retraining existing pre-trained ViTs and can be applied immediately to any Transformer-based architecture. Through extensive evaluations on multiple datasets, we found that DVT consistently and significantly improves existing state-of-the-art general models (e.g., +3.84 mIoU) in both semantic and geometric tasks. We hope our research encourages a re-evaluation of ViT design, especially regarding the naive use of positional embeddings.

3Deblurring 3D Gaussian Splatting is a novel neural field deblurring framework based on a recently proposed rasterization method, incorporating 3D Gaussian and rasterization. Utilizing small multi-layer perceptrons (MLPs), this product can reconstruct detailed, clear images from blurry images simultaneously with real-time rendering. The product increases point cloud density during training by employing a K-Nearest Neighbors (KNN) algorithm to add extra points and applies loose pruning to 3D Gaussian based on relative depth, preserving more 3D Gaussian information. Multiple experiments have validated the effectiveness of this product in deblurring.

FLUX.1-dev-Controlnet-Inpainting-Beta is an image restoration model developed by Alibaba's creative team, featuring significant improvements in image restoration. It supports direct processing and generation at 1024x1024 resolution without the need for additional upscaling, providing higher quality and more detailed outputs. The model has been fine-tuned to capture and reproduce more details in the restoration areas, with enhanced prompt explanations that allow for more precise control over the generated content.

FLUX-Controlnet-Inpainting is an image restoration tool released by the Alibaba Mama Creative Team, based on the FLUX.1-dev model. This tool utilizes deep learning technology to restore images, filling in missing sections and suitable for image editing and enhancement. It performs best at a resolution of 768x768, providing high-quality image restoration results. Currently, the tool is in the alpha testing phase, with future updates planned.

AuraSR-v2 is a GAN-based image super-resolution model designed for enlarging generated images, and it is a variant of the GigaGAN paper. The PyTorch implementation of this model is based on the unofficial lucidrains/gigagan-pytorch repository. It significantly enhances the resolution of images while preserving their quality, which is particularly important for applications requiring high-definition image outputs.

LighTDiff is a deep learning model designed to enhance surgical endoscope images under low-light conditions. Utilizing T-Diffusion technology, the model effectively increases the brightness and clarity of images, significantly contributing to surgical safety and efficiency. This technology has been accepted for early publication at the MICCAI2024 conference, and the code is open-source, available for research and practical applications.

Clik is an application designed specifically for sharing event photos, turning your phone into a digital disposable camera. It allows users to share photos with friends in real time without downloading the full application. Through AI technology, the app helps users quickly find photos they are involved in, and simplifies the sharing process in real life through in-app links and custom QR codes. Clik is suitable for various social occasions such as parties and weddings, helping users capture and preserve memorable moments.

Clipdrop Image upscaler is a handy tool that can improve the quality of compressed images. Its main advantages include fast image quality enhancement, a variety of image processing functionalities, and ease of use. Background information includes the product's positioning as a tool for improving image quality.

ComfyUI-SuperBeasts is an image processing application designed to enhance the dynamic range and visual appeal of images. It offers a set of adjustable parameters for finetuning HDR effects according to user preferences. The application features: * Adjust the intensity of shadows, highlights, and overall HDR effect; * Apply gamma correction to control overall brightness and contrast; * Enhance contrast and color saturation for more vibrant results; * Preserve color accuracy by processing images in the LAB color space; * Utilize brightness-based masks for targeted adjustments; * Blend adjusted luminosity with the original luminosity to achieve a balanced effect.

OMG (Once More Generalization) is an open-source image super-resolution tool that utilizes deep learning techniques to enhance image resolution. The project aims to improve image quality by using AI models, ensuring sharpness and detail even after enlargement.

Upscale.media plugins leverage advanced AI technology to offer image enlargement and enhancement features, simplifying your image processing workflow with just a few clicks. Thousands of users have already adopted Upscale.media to save time and achieve exceptional results.