AllocSplat: Spatial Allocation for Budget-Adaptive Feed-Forward Gaussian Splatting

Feed-forward 3D Gaussian Splatting reconstructs renderable scenes from a few images with known camera poses. Different storage and rendering limits call for different numbers of Gaussians. The challenge is to distribute a limited number of Gaussians across the scene while preserving local visual detail. We introduce AllocSplat, which uses 3D anchor points to determine where Gaussian groups are placed and how their spatial scales are set. A joint geometry–appearance rule selects these anchors from depth-based 3D candidates, considering both scene coverage and differences in visual content. A density-adaptive local decoder generates a fixed number of Gaussians per anchor, so the anchor count sets the total Gaussian count. It adapts each group's spatial scale to the local anchor density, using distances to nearby selected anchors to limit Gaussian sizes and offsets from the anchor. When the requested budget changes, the model selects the corresponding number of anchors and recomputes local scales and information shared across anchors before decoding. The same anchor point can thus generate different Gaussian groups at different budgets without changing the network weights. Experiments on DL3DV-140 show improved quality–count trade-offs across multiple Gaussian budgets. With four input views, AllocSplat achieves 0.99 dB higher PSNR than TokenGS using 85.9% fewer Gaussians, and exceeds ZipSplat by 0.29–1.65 dB at matched primitive counts.