Underwater scene reconstruction from degraded views can preserve visual degradation. Since paired enhanced 3D references are hard to obtain in real ocean scenes, underwater 3D methods largely rely on physics-based restoration. However, separating object radiance from medium effects is ill-posed and may leave residual artifacts. In contrast, we formulate underwater scene enhancement as learning the desired appearance of the scene and propose a two-stage framework called 3D-USE. Stage 1 builds a medium-aware Gaussian scene with MediumRBF, sharing medium estimates across nearby views and establishing stable geometry and visibility. Using a prior learned from external 2D enhancement pairs, Stage 2 applies Appearance Transition Consensus (ATC) to calibrate and aggregate view-wise appearance changes, defining the desired scene-level appearance transformation. Finally, an Underwater Bilateral Appearance Field (U-BAF) jointly adjusts object radiance and medium appearance to produce coherent enhanced appearance across viewpoints. Experiments show that 3D-USE improves novel-view enhancement and cross-view consistency while maintaining competitive reconstruction quality. The project page and code are available at https://bilityniu.github.io/3D-USE/.

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