mlsanityData to 14 Oct 2026

3D View Optimization for Improving Image Aesthetics

arXiv 2405.16443 ↗First posted 26 May 2024cs.CV cs.GRcited by 1

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Abstract (arXiv)

Achieving aesthetically pleasing photography necessitates attention to multiple factors, including composition and capture conditions, which pose challenges to novices. Prior research has explored the enhancement of photo aesthetics post-capture through 2D manipulation techniques; however, these approaches offer limited search space for aesthetics. We introduce a pioneering method that employs 3D operations to simulate the conditions at the moment of capture retrospectively. Our approach extrapolates the input image and then reconstructs the 3D scene from the extrapolated image, followed by an optimization to identify camera parameters and image aspect ratios that yield the best 3D view with enhanced aesthetics. Comparative qualitative and quantitative assessments reveal that our method surpasses traditional 2D editing techniques with superior aesthetics.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 26 references that are in the map. First posted on arXiv 26 May 2024.

Builds on

11 of 26 references.

References · 11

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  9. 2021Image Composition Assessment with Saliency-augmented Multi-pattern Poolingcited by 21
  10. 2023Beyond Image Borders: Learning Feature Extrapolation for Unbounded Image Compositioncited by 10
  11. 2021AutoPhoto: Aesthetic Photo Capture using Reinforcement Learningcited by 7

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