mlsanityData to 7 Oct 2026

From Pampas to Pixels: Fine-Tuning Diffusion Models for Ga'ucho Heritage

arXiv 2401.05520 ↗First posted 10 Jan 2024cs.CV cs.AI cs.CLcited by 3

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

Abstract (arXiv)

Generative AI has become pervasive in society, witnessing significant advancements in various domains. Particularly in the realm of Text-to-Image (TTI) models, Latent Diffusion Models (LDMs), showcase remarkable capabilities in generating visual content based on textual prompts. This paper addresses the potential of LDMs in representing local cultural concepts, historical figures, and endangered species. In this study, we use the cultural heritage of Rio Grande do Sul (RS), Brazil, as an illustrative case. Our objective is to contribute to the broader understanding of how generative models can help to capture and preserve the cultural and historical identity of regions. The paper outlines the methodology, including subject selection, dataset creation, and the fine-tuning process. The results showcase the images generated, alongside the challenges and feasibility of each concept. In conclusion, this work shows the power of these models to represent and preserve unique aspects of diverse regions and communities.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models. Builds on 13 of its 32 references that are in the map. First posted on arXiv 10 Jan 2024.

Builds on

13 of 32 references.

Closest ancestors · 1

Same direction, newest first

  1. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation25 Aug

Other references · 12

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  4. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  5. 2022MagicVideo: Efficient Video Generation With Latent Diffusion Modelscited by 463
  6. 2022Brain Imaging Generation with Latent Diffusion Modelscited by 267
  7. 2023DreamBooth3D: Subject-Driven Text-to-3D Generationcited by 235
  8. 2018Adversarial Audio Synthesiscited by 222
  9. 2022Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systemscited by 44
  10. 2022Opal: Multimodal Image Generation for News Illustrationcited by 36
  11. 2023Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesiscited by 32
  12. 2022AI Art in Architecturecited by 12

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Cited by year

Citing papers per year: 2024: 3.

3 papers.

  1. 2024Survey of Cultural Awareness in Language Models: Text and Beyondcited by 101
  2. 2024HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuningcited by 4
  3. 2024An Inpainting-Infused Pipeline for Attire and Background Replacementcited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2025Diffusion Models Through a Global Lens: Are They Culturally Inclusive?
  2. 2023Diffusion Based Augmentation for Captioning and Retrieval in Cultural Heritage
  3. 2024Illustrating Classic Brazilian Books using a Text-To-Image Diffusion Model
  4. 2024Generative AI in Vision: A Survey on Models, Metrics and Applications
  5. 2025Synthetic History: Evaluating Visual Representations of the Past in Diffusion Models
  6. 2024Cultural Heritage 3D Reconstruction with Diffusion Networks
  7. 2023Inspecting the Geographical Representativeness of Images from Text-to-Image Models
  8. 2023RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model