arXiv:2606.29379v1 Announce Type: cross Abstract: Gaussian splatting (GS) has garnered significant attention in VR/AR and digital content creation due to its explicit parameterization and efficient rendering capabilities. However, existing GS-based methods for deformable objects face two key limitations: (i) illumination is erroneously baked into textures, causing physically inconsistent responses under dynamic deformations and lighting changes; (ii) snapshot-based reconstruction restricts post-reconstruction material editing. To address these challenges, we propose Deformable and Relightable
The rapid advancement of Gaussian splatting for efficient rendering is hitting limitations in handling complex physical interactions and post-reconstruction editing.
Improving the physical realism and editability of 3D content generation directly impacts the fidelity and utility of VR/AR experiences and digital content creation tools.
This research addresses key limitations in existing Gaussian splatting methods, moving towards more physically consistent and flexible 3D scene representation.
- · VR/AR content creators
- · Digital content creation software developers
- · Gaming industry
- · 3D reconstruction firms
- · Methods reliant on 'baked-in' illumination
- · Static 3D capture techniques
- · Content requiring extensive manual post-production for lighting
More realistic and interactive virtual environments will become possible, enhancing immersion in VR/AR.
The cost and time required for producing high-fidelity animated and relightable 3D assets will decrease significantly.
This could accelerate the adoption of VR/AR for professional simulation, design, and entertainment, driving hardware demand.
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Read at arXiv cs.AI