HILITE: Human-in-the-loop Interactive Tool for Image Editing

Image editing tools have a plethora of commercial and creative applications — content-creation, digital photography, advertisements, graphic design, and development of educational media. The shortcomings of image editing software include difficulty of use and, for AI-based software, reliance on single image editing models, which often poses the dilemma of a tradeoff between image editing quality and user-friendliness. While the performances of individual image editing models have improved with their evolution over time, these singular models are often specialized on specific image editing tasks. In this work, we introduce HILITE, an open-source interactive image editing platform with a human-in-the-loop design that combines six diffusion-based image editing models. For one, HILITE’s accessible and easily-understandable user interface provides a straightforward user workflow from image input and prompt entry to selection of desired output. Secondly, the combination of several models with diverse specializations in turn allows HILITE to generalize on a wide variety of image editing tasks, essentially creating a "one-stop shop" for image editing. Third, HILITE iteratively takes user feedback, which both enhances the user experience and enables collection of crowd-sourced data for image editing. HILITE outperforms two major image editing softwares, OpenAI’s DALL•E 3 and Google’s Imagen 3, across two widely-user quantitative metrics for image editing evaluation. Considering the growing demand for readily-available and high-performing image editing tools, HILITE provides a novel platform design with multifaceted use cases in both business and academia. The platform can be found at https://platform.opennlplabs.org/ or https://platform-deployment.vercel.app/.

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Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10825916
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
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article

HILITE: Human-in-the-loop Interactive Tool for Image Editing

Subhadra Vadlamannati, Simran Khanuja, S Chang, Graham Neubig et al.
1 links
Generative Adversarial Networks and Image Synthesis
article

HILITE: Human-in-the-loop Interactive Tool for Image Editing

Subhadra Vadlamannati, Simran Khanuja, S Chang, Graham Neubig, Diyi Yang, Jayesh Patel, Anshu Sharma, Sophia Li, Yutong Zhang, Arya Pasumarthi, Ayush Bheemaiah, Eshaan Barkataki
article en

Abstract

Image editing tools have a plethora of commercial and creative applications — content-creation, digital photography, advertisements, graphic design, and development of educational media. The shortcomings of image editing software include difficulty of use and, for AI-based software, reliance on single image editing models, which often poses the dilemma of a tradeoff between image editing quality and user-friendliness. While the performances of individual image editing models have improved with their evolution over time, these singular models are often specialized on specific image editing tasks. In this work, we introduce HILITE, an open-source interactive image editing platform with a human-in-the-loop design that combines six diffusion-based image editing models. For one, HILITE’s accessible and easily-understandable user interface provides a straightforward user workflow from image input and prompt entry to selection of desired output. Secondly, the combination of several models with diverse specializations in turn allows HILITE to generalize on a wide variety of image editing tasks, essentially creating a "one-stop shop" for image editing. Third, HILITE iteratively takes user feedback, which both enhances the user experience and enables collection of crowd-sourced data for image editing. HILITE outperforms two major image editing softwares, OpenAI’s DALL•E 3 and Google’s Imagen 3, across two widely-user quantitative metrics for image editing evaluation. Considering the growing demand for readily-available and high-performing image editing tools, HILITE provides a novel platform design with multifaceted use cases in both business and academia. The platform can be found at https://platform.opennlplabs.org/ or https://platform-deployment.vercel.app/.

Open Society (CZ), Carnegie Mellon University (US), Stanford University (US)
Openalex Percentile: Top 74%
Generative Adversarial Networks and Image Synthesis
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