GaussLock embeds traps targeting position, scale, rotation, opacity, and color in 3D Gaussian models to degrade unauthorized fine-tunes while preserving authorized performance.
Learning to predict 3d objects with an interpolation-based differentiable renderer
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A differentiable optimization pipeline uses a contact graph and rigid-body simulation to jointly refine object poses and physical properties, producing physically valid 3D scene reconstructions from single-view RGB-D observations for cluttered environments.
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Immunizing 3D Gaussian Generative Models Against Unauthorized Fine-Tuning via Attribute-Space Traps
GaussLock embeds traps targeting position, scale, rotation, opacity, and color in 3D Gaussian models to degrade unauthorized fine-tunes while preserving authorized performance.
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Real-to-Sim for Highly Cluttered Environments via Physics-Consistent Inter-Object Reasoning
A differentiable optimization pipeline uses a contact graph and rigid-body simulation to jointly refine object poses and physical properties, producing physically valid 3D scene reconstructions from single-view RGB-D observations for cluttered environments.