Dataset Generation Model DatasetDM: Capable of Generating Accurate Perceptual Annotations

Second-level Product Image Synthesis: Krea AI Launches Custom Training Feature

AI Face Swapping Image Synthesis Framework FaceStudio Supports Multiple Image Synthesis

FaceStudio is an identity-preserving synthesis method that supports multiple image synthesis. FaceStudio achieves fast and efficient image generation through a direct feedforward mechanism, supporting multiple identity blending with significant advantages over baseline methods. Project address: https://icoz69.github.io/facestudio

New AI Framework DreamSync: Improving Text-to-Image Synthesis with Feedback from Image Understanding Models

DreamSync is a novel artificial intelligence framework that enhances text-to-image synthesis by generating candidate images and evaluating them using a visual question-answering model. DreamSync does not require manual annotations, modifications to model architectures, or reinforcement learning. The framework achieves significant alignment and visual appeal improvements on T2I models through a model-agnostic framework and feedback from visual language models. DreamSync successfully enhances the performance of SDXL and SD v1.4 T2I models.

Zhejiang University Researchers Introduce UrbanGIRAFFE to Solve 3D Image Synthesis Problems in Urban Scenes

UrbanGIRAFFE is a realistic image synthesis method proposed by researchers from Zhejiang University, focusing on controllable 3D perception image synthesis for urban scenes. This method achieves diverse control through controllable camera poses and scene content, utilizing semantic voxel grids and object layout decomposition to exhibit excellent controllability and fidelity. Comprehensive evaluations show that UrbanGIRAFFE surpasses 2D and 3D baselines on both synthetic and real datasets, particularly demonstrating superior background modeling and object editing on the KITTI-360 dataset.

CustomNet Technology Implementation for SD Product Image Integration

CustomNet is a technology jointly developed by Tsinghua University and the University of Tokyo, capable of integrating images of specified objects into newly generated images while retaining style and texture details. This technology achieves clear spatial relationships and perspective adjustments through its 3D new perspective synthesis capability, generating diverse outputs. CustomNet features flexible background control, allowing users to adjust the background harmoniously with objects through text descriptions or specific images. This technology can handle complex scene data from the real world, generating

New Image Synthesis Model LCM SD Reduces Image Generation Steps to 4!

Researchers have proposed a new image synthesis model called the Latent Consistency Model (LCM), which can generate high-resolution images with fewer inference steps. LCM is derived from the pre-trained Latent Diffusion Model (LDM) and can directly predict the solution of the probability flow ODE in latent space, reducing the number of iterations and computational load. LCM can be extracted from a pre-trained classifier-free guidance diffusion model, generating high-quality images during training. The paper also introduces a new fine-tuning method called Latent Consistency Fine-tuning.

OpenAI Releases DALL-E 3 Text-to-Image Model: Pushes the Limits in Detail and Prompt Fidelity with Full Integration into ChatGPT

DALL-E 3 is the latest version of the AI image synthesis model, fully integrated with ChatGPT. It renders images by closely following complex descriptions and processing text generated within images. DALL-E 3 can more effectively refine small details like hands, creating engaging images by default.