READ: Geometry-Guided Source Evidence Retrieval for Feed-Forward 3D Gaussian Splatting

Feed-forward 3D Gaussian splatting enables efficient novel view synthesis, but fine appearance details can be lost when source observations are encoded into Gaussian attributes. We present Reprojected Evidence Aggregation via Depth (READ), a lightweight rendering-time refinement module that uses a frozen Gaussian scene for both base rendering and geometry-guided retrieval of source appearance. READ combines posed source images with rendered RGB, depth, and accumulated alpha, without accessing the reconstruction model's internal features. Geometric reliability and learned source weights guide a bounded residual correction of the base rendering. With only 21K trainable parameters, READ improves novel-view fidelity and visual detail on DL3DV and RealEstate10K with low computational overhead. A single set of weights trained with one reconstruction model transfers across Gaussian reconstruction models, source-view counts, and datasets without retraining.