Core Insights - The article discusses the advancements in 3D Rendering & Reconstruction, particularly focusing on dynamic scene reconstruction and the integration of generative and editable 3D assets. It highlights the shift from merely rendering to creating and manipulating 3D environments, emphasizing the importance of efficiency, stability, and usability in real-world applications [2][60]. Group 1: Dynamic Scene and Temporal Reconstruction - Research in dynamic scene reconstruction aims to not only rebuild static geometries but also to express, compress, and render changes over time, effectively creating a 4D representation [2][4]. - The ReCon-GS framework improves training efficiency by approximately 15%, reduces memory usage by half while maintaining the same visual quality, and enhances the stability and robustness of free-viewpoint video (FVV) synthesis [5][6]. - ProDyG introduces a closed-loop system for tracking, mapping, and rendering, achieving dynamic SLAM-level camera tracking and improved stability for long sequences [10][12]. Group 2: Structural Innovations in Gaussian Splatting - The research focuses on making 3D Gaussian Splatting (3DGS) deployable and maintainable, ensuring that large scenes do not exceed memory limits and can run on mobile devices [20][21]. - The LODGE framework enhances the usability of large-scale 3DGS rendering by integrating Level-of-Detail (LOD) techniques, resulting in lower latency and memory usage [23][24]. - The Gaussian Herding across Pens method achieves near-lossless quality while retaining only about 10% of the original Gaussian data, providing a mathematically grounded approach to global compression [28][29]. Group 3: Generative and Editable 3D - The focus of generative and editable 3D research is to not only recreate real-world scenes but also to generate new assets, allowing for component splitting, rigging, animation, and material modification [42][44]. - The PhysX-3D framework emphasizes the generation of 3D assets that are not only visually appealing but also functional for physical simulations and robotics applications [46][47]. - The PartCrafter model enables the generation of modular 3D meshes that can be easily edited and rearranged, improving the efficiency of asset creation [48][50]. Group 4: Current Trends and Future Directions - The current research trends indicate a clear direction towards making dynamic reconstruction more efficient and stable, refining Gaussian methods for practical deployment, and enhancing the capabilities of 3D asset generation and editing [60]. - The evaluation criteria for these technologies are evolving to include not just clarity or scores but also latency, bandwidth, energy consumption, stability, and editability, which are crucial for real-world applications [60].