This paper presents an integrated rendering framework that enables stable cartoon-style rendering in 3D Gaussian Splatting (3DGS) scenes without explicit mesh reconstruction, while reinterpreting camera parameters as expressive controls for cartoon-style cinematography. Because 3DGS generates images through the accumulation of numerous Gaussian primitives, explicit surface depth or a single coherent geometric structure is not directly defined, which often leads to distant noise and visual instability when applying contour enhancement or camera effects. To address this limitation, we utilize the sparse point cloud obtained during the Structure-from-Motion (SfM) stage as proxy geometry to construct an auxiliary depth signal, referred to as proxy depth, which serves as a common cue for both distance-aware cartoon stylization and stylized camera control. The proxy depth is linearized and conservatively refined to reliably separate foreground and background regions, and distance-aware contour attenuation effectively suppresses undesired high-frequency edges in distant regions. Furthermore, this work redefines camera parameters such as focal length, depth of field, and projection not as constraints for photorealistic reproduction, but as expressive control variables for cartoon-style rendering, while maintaining compatibility with the cumulative rendering characteristics of 3DGS. This allows the framework to maintain consistent spatial emphasis and visual staging across viewpoint changes and varying scene compositions. In addition, a stabilization strategy is introduced during training by removing Gaussians with negligible screen-space contributions and constraining the total number of primitives, thereby improving the visual stability of both contour rendering and camera exaggeration. Experimental results demonstrate that the proposed framework achieves stable cartoon contour rendering and expressive camera motion simultaneously in the tested indoor and outdoor 3DGS scenes, while maintaining real-time performance under our experimental setup.
We address inverse rendering with 3D Gaussian Splatting (3DGS) by introducing explicit visibility modeling for relighting as well as material and light decomposition. Our approach augments the standard rasterized 3DGS pipeline with a sparse visibility oracle that estimates transmittance-weighted occlusion for Gaussian...
Sven Kluge, Oliver G. Staadt· Computer Science Research No...· 0 citations
Novel view synthesis from unconstrained outdoor photo collections remains challenging for robust 3D scene representation. 3D Gaussian Splatting (3DGS) achieves real-time rendering with high visual fidelity, yet its static formulation is vulnerable to illumination changes, weather variations, and transient occluders. Op...
Qiao Chen, Zhi-Cheng Li, Yao-Wen Chen et al.· 2026 6th International Confe...· 0 citations
Explicit 3D scene representations such as 3D Gaussian Splatting (3DGS) have recently enabled high-quality, real-time novel view synthesis. However, these methods assume static scenes, limiting realism in the presence of dynamic phenomena ubiquitous in real-world environments. While coherent motion (e.g., humans or vehi...
Kjell Keune, Florian Hahlbohm, Jannis Möller et al.· 0 citations
This work presents FixAnything, a single model for fixing a wide range of rendering artifacts by repurposing a pretrained video generative model, leveraging its implicit multi-view priors with only minimal modification and lightweight finetuning.
Khiem Vuong, D. Ramanan, Srinivasa G. Narasimhan· 1 citation
Experiments show that the hybrid Gaussian stippling method, coupled with a spatiotemporal reconstruction network trained on diverse scenes, generalizes to unseen scenes and enables interactive, temporally stable, and visually plausible rendering on mobile devices without retraining or preprocessing.
Zi-Jian Huang, Sui-Liang Mai, Chuan-Kun Zheng et al.· 0 citations
This work proposes Graph-Guided Adaptive Gaussian Splatting for Scene Stylization (GAGS)—an efficient 3D scene stylization framework for Gaussian Splatting representations that can generate high-quality stylizations and outperforms existing methods both qualitatively and quantitatively.
Haoyu Ren, Wei Xu, Qing Zhu et al.· International Conference on...· 0 citations
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