1. Introduction
The creation of realistic and complex 3D scenes is fundamental across various applications, including virtual reality, gaming, and film production. Existing methods for composing 3D objects into scenes often struggle with computational overhead, particularly when handling intricate lighting and geometric interactions. This paper proposes ComGS, a new framework designed to overcome these limitations by offering an efficient and high-quality solution for 3D object-scene composition. The primary model introduced and utilized in this article is ComGS, which employs Surface Octahedral Probes.
2. Related Work
Prior research in 3D scene generation has explored various techniques, from traditional mesh-based approaches to advanced neural rendering pipelines. Methods like volumetric representations and implicit neural representations have shown promise but often demand significant computational resources or suffer from slow inference times for complex scenes. Efforts to simplify scene integration have included pre-baked lighting solutions and simplified proxy geometries, yet these often compromise visual fidelity or flexibility. This work builds upon and differentiates from these methods by proposing a novel probe-based mechanism for efficient and dynamic scene synthesis.
3. Methodology
ComGS operates by utilizing Surface Octahedral Probes, which are strategically placed and oriented within the scene to capture and propagate local scene information. Each probe efficiently encodes geometric and appearance properties, including lighting and material interactions, for the surrounding environment in an octahedral representation. The composition process involves integrating individual 3D objects by adapting their appearance and interaction based on the nearest and most relevant probes. This allows for seamless blending and coherent scene illumination without requiring expensive global recalculations.
4. Experimental Results
Experiments were conducted to evaluate ComGS against state-of-the-art 3D composition methods across various scene complexities and object types. Key metrics included rendering speed, visual fidelity (e.g., PSNR, SSIM), and memory footprint. The findings consistently indicate that ComGS achieves significantly faster composition and rendering times while maintaining comparable or superior visual quality. For instance, scene generation speed improved by up to 2x, and memory usage was reduced by 30% on average, demonstrating its efficiency.
This table summarizes the performance comparison of ComGS with baseline methods across key metrics, illustrating its efficiency and quality advantages in 3D object-scene composition.
| Method | Composition Time (s) | PSNR (dB) | Memory Usage (MB) |
|---|---|---|---|
| Baseline A | 15.2 | 28.5 | 1200 |
| Baseline B | 10.5 | 29.1 | 950 |
| ComGS (Ours) | 7.8 | 30.2 | 650 |
5. Discussion
The results confirm that ComGS provides a robust and efficient solution for complex 3D object-scene composition, addressing critical bottlenecks in existing workflows. The significant improvements in both speed and memory efficiency, coupled with enhanced visual fidelity, highlight the practical utility of Surface Octahedral Probes. This approach opens new avenues for real-time 3D content creation and interactive applications where dynamic scene updates are crucial. Future work could explore adaptive probe placement strategies and integration with advanced physically-based rendering pipelines.