mlsanityData to 7 Oct 2026

An Inpainting-Infused Pipeline for Attire and Background Replacement

arXiv 2402.03501 ↗First posted 5 Feb 2024cs.CV cs.AI cs.CLcited by 1

On the map: Diffusion models → 3D, point cloud and scene generation

Abstract (arXiv)

In recent years, groundbreaking advancements in Generative Artificial Intelligence (GenAI) have triggered a transformative paradigm shift, significantly influencing various domains. In this work, we specifically explore an integrated approach, leveraging advanced techniques in GenAI and computer vision emphasizing image manipulation. The methodology unfolds through several stages, including depth estimation, the creation of inpaint masks based on depth information, the generation and replacement of backgrounds utilizing Stable Diffusion in conjunction with Latent Consistency Models (LCMs), and the subsequent replacement of clothes and application of aesthetic changes through an inpainting pipeline. Experiments conducted in this study underscore the methodology's efficacy, highlighting its potential to produce visually captivating content. The convergence of these advanced techniques allows users to input photographs of individuals and manipulate them to modify clothing and background based on specific prompts without manually input inpainting masks, effectively placing the subjects within the vast landscape of creative imagination.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 23 of its 38 references that are in the map. First posted on arXiv 5 Feb 2024.

Builds on

23 of 38 references.

Closest ancestors · 2

Same direction, newest first

  1. 2022SmartBrush: Text and Shape Guided Object Inpainting with Diffusion Model9 Dec
  2. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Models24 Jan

Other references · 21

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  5. 2020Denoising Diffusion Implicit Modelscited by 9,655
  6. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  7. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
  8. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  9. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,286
  10. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,231
  11. 2021Vision Transformers for Dense Predictioncited by 1,789
  12. 2023Consistency Modelscited by 1,778
9 more
  1. 2016WaveNet: A Generative Model for Raw Audiocited by 1,710
  2. 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,484
  3. 2022Diffusion Models in Vision: A Surveycited by 1,008
  4. 2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 924
  5. 2023Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inferencecited by 826
  6. 2017Tacotron: Towards End-to-End Speech Synthesiscited by 487
  7. 2019MirrorGAN: Learning Text-to-image Generation by Redescriptioncited by 176
  8. 2017Perceptual Adversarial Networks for Image-to-Image Transformationcited by 42
  9. 2024From Pampas to Pixels: Fine-Tuning Diffusion Models for Ga'ucho Heritagecited by 3

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Cited by year

Citing papers per year: 2024: 1.

1 paper.

  1. 2024MiraGe: Editable 2D Images using Gaussian Splattingcited by 12

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  1. 2025Generative AI for Film Creation: A Survey of Recent Advances
  2. 2025InstructVTON: Optimal Auto-Masking and Natural-Language-Guided Interactive Style Control for Inpainting-Based Virtual Try-On
  3. 2024Automatic Generation of Fashion Images using Prompting in Generative Machine Learning Models
  4. 2025Fine-Grained Customized Fashion Design with Image-into-Prompt benchmark and dataset from LMM
  5. 2024Recursive InPainting (RIP): how much information is lost under recursive inferences?
  6. 2025SAGI: Semantically Aligned and Uncertainty Guided AI Image Inpainting
  7. 2024FashionSD-X: Multimodal Fashion Garment Synthesis using Latent Diffusion
  8. 2023Taming the Power of Diffusion Models for High-Quality Virtual Try-On with Appearance Flow