3D Gaussian assets are easy to copy, transform, and redistribute. This is a feature, not a flaw—but it introduces serious challenges for creators and organizations.

Unlike traditional 3D models, splat scenes:

• Do not have obvious surface structure to watermark

• Are often shared as raw data

• Can survive format changes and reprocessing

Once an asset leaves its creator’s environment, attribution can be lost entirely.

In a world where digital assets increasingly carry real economic and cultural value, this lack of provenance becomes a problem.

Existing protection strategies were designed for other media:

• File encryption restricts access but breaks real-time workflows

• DRM systems rely on platforms, not data

• Mesh watermarking does not translate to volumetric splats

Most approaches either degrade performance, limit usability, or fail entirely once the asset is transformed.

What is needed is not restriction, but resilience—a way for ownership information to persist naturally within the asset itself.

GuardSplat embeds resilient, invisible ownership signals directly into 3D Gaussian representations, allowing assets to carry provenance without sacrificing performance or openness.

Rather than treating watermarking as an external layer, GuardSplat operates at the level of the representation itself.

Gaussian splats are defined by parameters such as position, scale, orientation, and appearance. GuardSplat subtly modulates these parameters in a controlled way, encoding ownership information without altering the perceived scene.

Because this information is distributed across many Gaussians:

• It does not rely on a single identifiable marker

• It survives common transformations

• It remains invisible during normal rendering

The result is an asset that looks and behaves the same—but carries a persistent signature.

GuardSplat is not designed to lock assets down or prevent viewing. Instead, it provides accountability.

It helps protect against:

• Unauthorized redistribution

• Asset laundering through reprocessing

• Ownership disputes

It does not:

• Prevent copying

• Act as DRM

• Restrict legitimate use

This distinction matters. GuardSplat is about traceability, not control.

As Gaussian Splatting becomes more widespread, new markets and workflows emerge:

• Asset marketplaces

• Shared capture pipelines

• AI training on 3D data

All of these depend on trust—between creators, platforms, and users.

Without built-in provenance, scaling these ecosystems becomes risky. GuardSplat provides a foundation for that trust without imposing centralized control.

Perhaps the most important aspect of GuardSplat is philosophical.

It does not attempt to close systems or limit experimentation. Instead, it acts as quiet infrastructure—supporting attribution, enabling verification, and preserving openness.

In that sense, GuardSplat aligns closely with the ethos that made Gaussian Splatting powerful in the first place: flexible, efficient, and compatible with modern workflows.

3D Gaussian Splatting represents a shift in how we digitize the world. GuardSplat complements that shift by ensuring that as assets move freely, their origins are not lost.

As tooling, standards, and adoption evolve, protection will not be something bolted on at the end—but something embedded from the start.

In the next phase of 3D content creation, trust will be just as important as fidelity.