SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer
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Updated
Nov 10, 2025 - Python
SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer
LTX-Video Support for ComfyUI
Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)
[AAAI 2025]👔IMAGDressing👔: Interactive Modular Apparel Generation for Virtual Dressing. It enables customizable human image generation with flexible garment, pose, and scene control, ensuring high fidelity and garment consistency for virtual dressing.
The most advanced Nano Banana image generator and editor application. Your central hub for AI image generation and revisions. Intuitive UI features reference images, editing with image masks, version history, and more. Powered by Gemini 2.5 Flash images API.
Colab notebook for Stable Diffusion Hyper-SDXL.
[CVPR 2025 Oral]Infinity ∞ : Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis
Rich-Text-to-Image Generation
The Paper List of Large Multi-Modality Model (Perception, Generation, Unification), Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Insight.
(Accepted by IJCV) Liquid: Language Models are Scalable and Unified Multi-modal Generators
AutoStudio: Crafting Consistent Subjects in Multi-turn Interactive Image Generation
Awesome Unified Multimodal Models
UniWorld: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
[NeurIPS-2023] Annual Conference on Neural Information Processing Systems
Faster generation with text-to-image diffusion models.
[NeurIPS'23] "MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing".
[NeurIPS 2024] ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization
Full-Stack ASP.NET Core and Next.js to create AI-Generated Short Videos with Captions using only free resources
[ICCV 2023 Oral, Best Paper Finalist] ITI-GEN: Inclusive Text-to-Image Generation
[CVPR 2025] Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization
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