In a competitive landscape dominated by powerful photo editing software, Apple has recently introduced a notable update to its Photos app with a new AI feature called Clean Up. Released with macOS Sequoia (version 15.1), this tool is designed to remove unwanted objects from images, positioning itself directly against similar offerings from Adobe, specifically in Photoshop and Lightroom. As both companies strive to enhance user experience through generative AI, many are left wondering: which tool is better? This article explores a comparative analysis between Apple’s Clean Up and Adobe’s Generative Remove, going through several test images for a head-to-head performance evaluation.
The Clean Up feature in Apple Photos is intuitive, gaining attention for its ability to effectively eliminate distractions in photographs. While users might be more familiar with its capabilities on iOS devices, this latest release brings the cleaning power to the desktop platform. Utilizing advanced AI, Clean Up not only removes unwanted elements but sometimes suggests objects to delete, a feature that diverges from Adobe’s approach, which relies heavily on user input and selection.
In a recent test, I used both platforms to remove various elements from six different photographs to evaluate their effectiveness. For the first image, power lines were removed from a scenic landscape. The results left by Adobe Generative Remove were disappointing, resulting in a noisy, pixelated image that suggested the AI struggled with textures. Conversely, Apple’s Clean Up delivered a flawless removal, presenting a clean, clear picture unmarred by artifacts. Here, Apple decisively took the win.
Next, I tasked both applications with removing two individuals standing at a platform’s edge—a common scenario for an AI tool. Adobe displayed an odd reluctance to leave the area blank, managing to remove one person effectively while mistakenly filling the void with an incongruous post. On the other hand, Apple Clean Up, while creating some visual clutter in the background, accomplished the task without introducing nonsensical elements. Again, a clear victory for Apple.
The third photograph involved removing individuals so that the focus could be shifted to a main subject in a cultural setting. Adobe again faltered, displaying a misunderstanding of the task that hindered the overall outcome. Apple’s approach yielded a better reflection of surrounding elements but showed signs of minor smudging. Despite its imperfections, Apple emerged as the preferred choice.
A more complex challenge presented itself when I attempted to erase a boat from a river scene. Here, the results resulted in a tie. Adobe managed an acceptable output, yet the pixels were smudgy and less distinct. On the contrary, Apple created sharper details, albeit with odd pixel duplication. Neither company came out squarely on top in this particular instance.
When I concentrated on a challenging subject—a person on an escalator—results were again favorable for Apple. Clean Up generated an accurate replication of the background, though a shadow remained where the person had stood. Adobe, however, showcased significant errors, including floating artifacts and chaotic sections that rendered the result unusable without additional editing.
Lastly, a test was performed using Adobe’s Generative Fill tool, which operates differently from Generative Remove. The outcome was dismal; the AI produced bizarrely unacceptable suggestions, emphasizing a fundamental issue with Adobe’s generative abilities. In contrast, Apple’s Clean Up recognized the prompt efficiently, reestablishing its advantage.
In light of the results, it appears Adobe’s recent updates to its AI-driven features may result in unsatisfactory outputs that do not meet user expectations. The inconsistency of Adobe’s results raises questions about the effectiveness of its updates, despite reassurances from the company regarding their commitment to improving performance. Meanwhile, Apple’s Clean Up feature demonstrates a solid understanding of its role and delivers predictable results—each operation yielding the same high-quality output without unnecessary complications.
As Apple continues refining its photo editing features, the call for a resurgence of programs like Aperture could grow stronger among creative users. The stark contrast in performance between these two tools indicates not just a competitive edge for Apple but also a cautionary tale regarding the implementation of AI technology in software products. For users looking for a reliable and effective tool for object removal in photography, Apple’s Clean Up appears to be a compelling option that outshines Adobe’s currently unreliable offerings. With the added benefit of being free for macOS users—a stark contrast to Adobe’s subscription model—the momentum appears to be in Apple’s favor at this juncture.