mlsanityData to 14 Oct 2026

Clutter Detection and Removal by Multi-Objective Analysis for Photographic Guidance

arXiv 2507.14553 ↗First posted 19 Jul 2025cs.CV cs.HCcited by 0

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Abstract (arXiv)

Clutter in photos is a distraction preventing photographers from conveying the intended emotions or stories to the audience. Photography amateurs frequently include clutter in their photos due to unconscious negligence or the lack of experience in creating a decluttered, aesthetically appealing scene for shooting. We are thus motivated to develop a camera guidance system that provides solutions and guidance for clutter identification and removal. We estimate and visualize the contribution of objects to the overall aesthetics and content of a photo, based on which users can interactively identify clutter. Suggestions on getting rid of clutter, as well as a tool that removes cluttered objects computationally, are provided to guide users to deal with different kinds of clutter and improve their photographic work. Two technical novelties underpin interactions in our system: a clutter distinguishment algorithm with aesthetics evaluations for objects and an iterative image inpainting algorithm based on generative adversarial nets that reconstructs missing regions of removed objects for high-resolution images. User studies demonstrate that our system provides flexible interfaces and accurate algorithms that allow users to better identify distractions and take higher quality images within less time.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 41 of its 120 references that are in the map. First posted on arXiv 19 Jul 2025.

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41 of 120 references.

References · 41

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29 more
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