DSD Diffusion Self-Distillation

Overview

Diffusion Self-Distillation (DSD) fixes a big problem in AI image generation-keeping a subject looking right across different settings. Regular models struggle with this because they don’t always have enough good data to work with. DSD changes that by training itself using a pre-trained diffusion model, so it learns to generate better, more consistent images without extra data or test-time tweaks.

DSD uses a pre-trained AI model to create its own dataset It starts by generating a grid of images then picks the best ones using a Visual-Language Model (VLM). This refined dataset is used to fine-tune the original model turning it into a generator that responds to both text and image prompts That means you can ask for a specific person or object in a new setting and get a high-quality image that still looks like the original.

Most zero-shot image generators can’t keep fine details consistent and per-instance tuning methods take too long DSD offers the best of both worlds-high-quality results with no extra work at test time It competes with tuned models but works much faster making it a great tool for creative projects.

Licenced under Apache 2.0