An Inpainting-Infused Pipeline for Attire and Background Replacement
<|reference_start|>An Inpainting-Infused Pipeline for Attire and Background Replacement: 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.<|reference_end|>
@article{perche-mahlow2024an,
    title={An Inpainting-Infused Pipeline for Attire and Background Replacement},
    author={Felipe Rodrigues Perche-Mahlow and Andr'e Felipe-Zanella and William
  Alberto Cruz-Casta~neda and Marcellus Amadeus},
    journal={arXiv preprint arXiv:2402.03501},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.03501},
    primaryClass={cs.CV cs.AI cs.CL}
}