Understanding Generative AI Capabilities in Everyday Image Editing Tasks
Authors: name: Mohammad Reza Taesiri; name: Brandon Collins; name: Logan Bolton; name: Viet Dac Lai; name: Franck Dernoncourt; name: Trung Bui; name: Anh Totti Nguyen
Published: 2025-05-22 03:35:15

Abstract: Generative AI (GenAI) holds significant promise for automating everyday image
editing tasks, especially following the recent release of GPT-4o on March 25,
2025. However, what subjects do people most often want edited? What kinds of
editing actions do they want to perform (e.g., removing or stylizing the
subject)? Do people prefer precise edits with predictable outcomes or highly
creative ones? By understanding the characteristics of real-world requests and
the corresponding edits made by freelance photo-editing wizards, can we draw
lessons for improving AI-based editors and determine which types of requests
can currently be handled successfully by AI editors? In this paper, we present
a unique study addressing these questions by analyzing 83k requests from the
past 12 years (2013-2025) on the Reddit community, which collected 305k
PSR-wizard edits. According to human ratings, approximately only 33% of
requests can be fulfilled by the best AI editors (including GPT-4o,
Gemini-2.0-Flash, SeedEdit). Interestingly, AI editors perform worse on
low-creativity requests that require precise editing than on more open-ended
tasks. They often struggle to preserve the identity of people and animals, and
frequently make non-requested touch-ups. On the other side of the table, VLM
judges (e.g., o1) perform differently from human judges and may prefer AI edits
more than human edits. Code and qualitative examples are available at:
https://psrdataset.github.io