BiGS: Bidirectional Gaussian Primitives for Relightable 3D Gaussian Splatting (2408.13370v1)

Abstract: We present Bidirectional Gaussian Primitives, an image-based novel view synthesis technique designed to represent and render 3D objects with surface and volumetric materials under dynamic illumination. Our approach integrates light intrinsic decomposition into the Gaussian splatting framework, enabling real-time relighting of 3D objects. To unify surface and volumetric material within a cohesive appearance model, we adopt a light- and view-dependent scattering representation via bidirectional spherical harmonics. Our model does not use a specific surface normal-related reflectance function, making it more compatible with volumetric representations like Gaussian splatting, where the normals are undefined. We demonstrate our method by reconstructing and rendering objects with complex materials. Using One-Light-At-a-Time (OLAT) data as input, we can reproduce photorealistic appearances under novel lighting conditions in real time.

• The paper introduces a novel method for enhancing 3D Gaussian splatting by integrating intrinsic light decomposition for dynamic relighting.
• It employs bidirectional spherical harmonics to efficiently model both diffuse and specular light scattering in complex materials.
• Experimental results validate real-time rendering and novel view synthesis, demonstrating the method’s applicability in interactive environments.

Overview of "BiGS: Bidirectional Gaussian Primitives for Relightable 3D Gaussian Splatting"

This paper introduces a novel technique for relightable 3D rendering using a method termed Bidirectional Gaussian Primitives (BiGS). The authors present an approach to represent and render 3D objects composed of surface and volumetric materials under dynamic illumination conditions. The key innovation lies in the integration of light intrinsic decomposition into the Gaussian splatting framework, which allows for real-time relighting of 3D objects.

Key Contributions

1. Novel Relightable Gaussian Primitives: The proposed method enhances the Gaussian splatting framework by accounting for both surface and volumetric appearances, without relying on specific surface normal-related reflectance functions. This is achieved through a bidirectional representation of light and view-dependent scattering functions.
2. Bidirectional Spherical Harmonics: The authors employ bidirectional spherical harmonics to represent the light-dependent scattering functions, enabling efficient modeling and rendering of complex materials under varying lighting conditions. This approach is conducive to capturing both diffuse and specular reflections, and is particularly adept at handling objects with fuzzy or translucent materials.
3. Optimization Method: The paper details a robust optimization method for extracting relightable Gaussian primitives from One-Light-At-a-Time (OLAT) datasets. The proposed method incorporates physics-inspired regularization terms to ensure stable optimization and minimize decomposition ambiguities.

Methodology

The methodology revolves around enhancing the traditional Gaussian splatting approach to include dynamic lighting conditions. This is essential for applications in interactive environments such as virtual production, video games, and mixed reality, where lighting conditions can vary dramatically.

1. Intrinsic Light Decomposition: The color of each Gaussian is decomposed into direct and indirect illumination components. The direct component is further divided into diffuse and directional scattering parts, allowing for detailed modeling of light interactions within the scene.
2. Bidirectional Spherical Harmonics Representation: Spherical harmonics are used to compactly represent the light interaction functions, with a focus on ensuring reciprocity and energy conservation. This representation reduces computational complexity while maintaining high fidelity in light transport modeling.
3. Training on OLAT Data: The model is trained on synthetic OLAT datasets as well as captured data from a light stage. The training process includes specific regularization techniques to enforce physical plausibility in the light decomposition.

Experimental Results

The authors validate their approach with a series of experiments demonstrating real-time relighting and novel view synthesis capabilities. Strong numerical results are presented on various types of materials, including glossy surfaces, fuzzy objects, and translucent volumes. For instance, the paper includes impressive relighting examples of a translucent dragon model and a furball model, showcasing the ability to adapt to different lighting conditions while preserving material-specific appearance details.

Implications

The implications of this research are significant for both practical and theoretical advancements in the field of computer graphics and visualization:

1. Practical: The method enables high-fidelity, real-time rendering of complex materials under dynamic lighting, which can be directly applied to interactive environments and realistic scene reconstructions.
2. Theoretical: The introduction of bidirectional spherical harmonics for light scattering functions provides a new avenue for efficient light transport modeling. This work may inspire further exploration into even more compact and versatile representations.

Future Directions

The authors acknowledge some limitations and propose future research directions, including:

• Enhancing the robustness of intrinsic decomposition, particularly in challenging lighting scenarios.
• Exploring alternative basis functions to better capture high-frequency light transport effects.
• Incorporating material-specific models to further refine the scattering functions.

In summary, the paper presents a substantial advancement in the field of relightable 3D rendering, particularly for interactive and real-time applications. The integration of bidirectional Gaussian primitives with spherical harmonics lays a strong foundation for future research and development in dynamic scene relighting.