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Review paper details AI for underwater visual enhancement and 3D reconstruction

A new review paper published on arXiv addresses the challenges in underwater visual enhancement and 3D reconstruction. It details the physical models and surveys various methods, from traditional techniques to advanced data-driven approaches like Neural Radiance Fields and 3D Gaussian Splatting. The paper also includes quantitative and qualitative evaluations of current algorithms and outlines future research directions in underwater vision. AI

RANK_REASON This is a review paper on a specific topic within computer vision and AI. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Guoxi Huang, Haoran Wang, Brett Seymour, Evan Kovacs, John Ellerbroc, Dave Blackham, Nantheera Anantrasirichai ·

    Visual enhancement and 3D representation for underwater scenes: a review

    arXiv:2505.01869v2 Announce Type: replace Abstract: Underwater visual enhancement (UVE) and underwater 3D reconstruction pose significant challenges in computer vision and AI-based tasks due to complex imaging conditions in aquatic environments. Despite the development of numerou…