Observation-Aware QIM for Gaussian Splats

When one 3D Gaussian-splatting asset is released to several recipients, a leaked copy should reveal which release it came from. Releases share geometry exactly, so the identifier can live only in the spherical-harmonic (SH) colour coefficients, where it must stay invisible yet survive re-export. Existing marks need trained decoders, and a direct write budgets its change in coefficient distance although camera sensitivity spans a median 7.2 orders of magnitude, leaving margins too thin for 8-bit export. We instead spend the budget in the renderer's own error metric, placing the mark where cameras barely look. Observation-aware quantization index modulation (QIM) solves each keyed quantization write in closed form in a metric built from compositing weights, and a compositing inequality bounds the image error of the complete write on the declared cameras, certifying each write before release. On fourteen scenes at matched training error, exact recovery after 8-bit export rises from 10/70 to 70/70 over Euclidean and diagonal controls, at higher held-out error; at a matched 48-bit payload, every identifier survives half-pruning at a marking cost of $.0005$ dB, against $3.99$ dB for GaussianMarker. Float16 coordinates, SH truncation, and a keyless recipient holding the declared cameras remain failure modes. These results show that solving the write in the renderer's metric lets a training-free mark survive export, and they give native 3D assets a certified release identifier with measured limits.