mlsanityData to 7 Oct 2026

Layered Diffusion Model for One-Shot High Resolution Text-to-Image Synthesis

arXiv 2407.06079 ↗First posted 8 Jul 2024cs.CV cs.AIcited by 0

On the map: Diffusion models → Image generation, text-to-image and editing

Abstract (arXiv)

We present a one-shot text-to-image diffusion model that can generate high-resolution images from natural language descriptions. Our model employs a layered U-Net architecture that simultaneously synthesizes images at multiple resolution scales. We show that this method outperforms the baseline of synthesizing images only at the target resolution, while reducing the computational cost per step. We demonstrate that higher resolution synthesis can be achieved by layering convolutions at additional resolution scales, in contrast to other methods which require additional models for super-resolution synthesis.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models. Builds on 7 of its 12 references that are in the map. First posted on arXiv 8 Jul 2024.

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7 of 12 references.

Closest ancestors · 4

Same direction, newest first

  1. 2023RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Paths29 May
  2. 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers2 Nov
  3. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding23 May
  4. 2022Hierarchical Text-Conditional Image Generation with CLIP Latents13 Apr

Other references · 3

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2023Simple diffusion: End-to-end diffusion for high resolution imagescited by 413

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  1. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
  2. 2023KOALA: Empirical Lessons Toward Memory-Efficient and Fast Diffusion Models for Text-to-Image Synthesis
  3. 2024Enhancing Semantic Fidelity in Text-to-Image Synthesis: Attention Regulation in Diffusion Models
  4. 2025Exploring the Deep Fusion of Large Language Models and Diffusion Transformers for Text-to-Image Synthesis
  5. 2024DiffuseHigh: Training-free Progressive High-Resolution Image Synthesis through Structure Guidance
  6. 2022Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation
  7. 2024MegaFusion: Extend Diffusion Models towards Higher-resolution Image Generation without Further Tuning
  8. 2024Scaling Rectified Flow Transformers for High-Resolution Image Synthesis