DeferredGS represents a critical advancement in accelerating NeRF’s capabilities:

• Overcomes current Gaussian splatting limitations for independent editing of texture and lighting.
• Models illumination with a learnable environment map and introduces attributes on Gaussians for a more realistic depiction.
• Utilizes deferred shading to achieve enhanced relighting effects and to improve texture and shape consistency.

The research solidifies DeferredGS as an imperative addition to the computational toolkit for rendering and editing 3D scenes. It promises notable advancements in the realism of computer-generated imagery and sheds light on the synergy between different domains – from computer graphics to artificial intelligence. Read More