HDGS: Textured 2D Gaussian Splatting for Enhanced Scene Rendering (2412.01823v1)

Abstract: Recent advancements in neural rendering, particularly 2D Gaussian Splatting (2DGS), have shown promising results for jointly reconstructing fine appearance and geometry by leveraging 2D Gaussian surfels. However, current methods face significant challenges when rendering at arbitrary viewpoints, such as anti-aliasing for down-sampled rendering, and texture detail preservation for high-resolution rendering. We proposed a novel method to align the 2D surfels with texture maps and augment it with per-ray depth sorting and fisher-based pruning for rendering consistency and efficiency. With correct order, per-surfel texture maps significantly improve the capabilities to capture fine details. Additionally, to render high-fidelity details in varying viewpoints, we designed a frustum-based sampling method to mitigate the aliasing artifacts. Experimental results on benchmarks and our custom texture-rich dataset demonstrate that our method surpasses existing techniques, particularly in detail preservation and anti-aliasing.

• The paper presents a novel frustum-based sampling technique that reduces aliasing in 2D Gaussian Splatting while achieving superior detail preservation.
• It introduces optimizable per-surfel texture maps to separate geometry from appearance, strengthening high-frequency texture retention.
• A per-ray sorting mechanism combined with Fisher information-based pruning optimizes rendering consistency and memory efficiency.

Analysis of HDGS: Textured 2D Gaussian Splatting for Enhanced Scene Rendering

The paper delineates the development of HDGS, an innovative approach to refine the capabilities of 2D Gaussian Splatting (2DGS) in rendering intricate scene details while mitigating anti-aliasing issues. In neural rendering contexts, particularly in tasks like novel view synthesis and geometry reconstruction, 2DGS has demonstrated efficiency by utilizing 2D Gaussian surfels in representing complex scenes. However, challenges such as aliasing artifacts and the preservation of high-resolution texture details at various viewing distances and resolutions persist. This paper offers a structured solution to these issues.

Key Contributions

1. Frustum-based Sampling Technique: To address aliasing artifacts when rendering from arbitrary viewpoints and multiple resolutions, the authors present a frustum-based sampling technique. This technique conceptualizes each pixel as corresponding to a light frustum sampling over a volume, reducing aliasing artifacts especially in high-frequency regions. By contrast with previous methodologies involving projection approximation, this technique adapts the sampling approach to better suit the precise projections entailed in 2DGS.
2. Optimizable Per-Surfel Texture Maps: The novel integration of per-surfel texture maps, each aligned with the Gaussian primitives, facilitates disentangling geometry from appearance. This advancement allows for the preservation of high-frequency detail that standard 2DGS cannot resolve. The refinement comes by allowing a more complex and customizable appearance description for each surfel.
3. Per-Ray Sorting: Recognizing that 2DGS faces popping artifacts due to its global per-view sorting approach, this method employs a per-ray sorting strategy. This refinement diminishes inconsistencies in rendering that stem from differences in primitive ordering across views by sorting surfels along each ray.
4. Fisher Information-Based Pruning: In response to the memory demands introduced by per-surfel texturing, the authors utilize a Fisher-information-based pruning technique. This method enhances the efficiency of rendering by strategically removing Gaussians with high uncertainty, thus optimizing the memory use without compromising detail.

Experimental Validation

The authors validate their method by conducting extensive experimentation on both standard benchmarks and a custom texture-rich dataset. The results consistently show that HDGS outperforms existing techniques in terms of detail preservation and anti-aliasing. More specifically:

• Rendering Quality: Experimental outcomes demonstrate superior rendering quality across varying resolutions and distances, with significant improvements in PSNR, SSIM, and LPIPS scores when compared to the baseline 2DGS.
• Geometry Consistency: The integration of per-ray sorting substantively reduces the popping artifacts, enhancing the geometric consistency and rendering fidelity of high-frequency details.

Implications and Future Directions

The paper's contributions suggest far-reaching implications for both the theory and practice of neural rendering. By enriching the expressive capacity of 2D Gaussian primitives with textural intricacies, and coupling that with enhanced computational strategies, the method paves the way for richer, more detailed renderings using efficient representations. This is particularly impactful for applications demanding fine detail in rendered imagery, such as in digital content creation and augmented reality.

Future work could explore further integration of optimization techniques to manage computational cost, especially relevant for real-time rendering applications. Moreover, extending the adaptive sampling strategies could bolster robustness across even more challenging scenarios, potentially enhancing the adaptability of this framework to other domains utilizing neural rendering.

In summary, this paper provides an insightful and technically robust enhancement to 2D Gaussian Splatting methodologies, significantly raising the bar in the domain of detailed scene rendering, with strong prospects for broad applicability and further innovation.