F⁴Splat: Feed-Forward Predictive Densification for Feed-Forward 3D Gaussian Splatting

Feed-forward 3D Gaussian Splatting methods enable single-pass reconstruction and real-time rendering. However, they typicallyadopt rigid pixel-to-Gaussian or voxel-to-Gaussian pipelines that uni-formly allocate Gaussians, leading to redundant Gaussians across views.Moreover, they lack an effective mechanism to control the total numberof Gaussians while maintaining reconstruction fidelity. To address theselimitations, we present F4 Splat, which performs Feed-Forward predic-tive densification for Feed-Forward 3D Gaussian Splatting, introduc-ing a densification-score-guided allocation strategy that adaptively dis-tributes Gaussians according to spatial complexity and multi-view over-lap. Our model predicts per-region densification scores to estimate therequired Gaussian density and allows explicit control over the final Gaus-sian budget without retraining. This spatially adaptive allocation reducesredundancy in simple regions and minimizes duplicate Gaussians acrossoverlapping views, producing compact yet high-quality 3D representa-tions. Extensive experiments demonstrate that our model achieves su-perior novel-view synthesis performance compared to prior uncalibratedfeed-forward methods, while using significantly fewer Gaussians.