An Inpainting-Infused Pipeline for Attire and Background Replacement
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866929234704859136 |
|---|---|
| author | Perche-Mahlow, Felipe Rodrigues Felipe-Zanella, André Cruz-Castañeda, William Alberto Amadeus, Marcellus |
| author_facet | Perche-Mahlow, Felipe Rodrigues Felipe-Zanella, André Cruz-Castañeda, William Alberto Amadeus, Marcellus |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_03501 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | An Inpainting-Infused Pipeline for Attire and Background Replacement Perche-Mahlow, Felipe Rodrigues Felipe-Zanella, André Cruz-Castañeda, William Alberto Amadeus, Marcellus Computer Vision and Pattern Recognition Artificial Intelligence Computation and Language 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. |
| title | An Inpainting-Infused Pipeline for Attire and Background Replacement |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2402.03501 |