Stable Diffusion

'Stable Diffusion' is a widely-used text-to-image diffusion model that serves as a benchmark for evaluating the performance of generative models in image generation.

Papers using Stable Diffusion (10)

Training-Free Debiasing of Diffusion Models via CLIP-Guided Denoising Optimization2026HiWave: Training-Free High-Resolution Image Generation via Wavelet-Based Diffusion Sampling2025Image Interpolation with Score-based Riemannian Metrics of Diffusion Models2025Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models2023 · 583 citesFaster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference2023 · 6 citesConcept Algebra for (Score-Based) Text-Controlled Generative Models2023 · 5 citesAccelerating Parallel Sampling of Diffusion Models2024 · 4 citesApplying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models2024 · 1 citesDiffusion Tuning: Transferring Diffusion Models via Chain of Forgetting2024Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow2024