Bézier Splatting for Fast and Differentiable Vector Graphics Rendering
Xi Liu, Chaoyi Zhou, Nanxuan Zhao, Siyu Huang
摘要
Differentiable vector graphics (VGs) are widely used in image vectorization and vector synthesis, while existing representations are costly to optimize and struggle to achieve high-quality rendering results for high-resolution images. This work introduces a new differentiable VG representation, dubbed Bézier Splatting, that enables fast yet high-fidelity VG rasterization. Bézier Splatting samples 2D Gaussians along Bézier curves, which naturally provide positional gradients at object boundaries. Thanks to the efficient splatting-based differentiable rasterizer, Bézier Splatting achieves 30x and 150x faster per forward and backward rasterization step for open curves compared to DiffVG. Additionally, we introduce an adaptive pruning and densification strategy that dynamically adjusts the spatial distribution of curves to escape local minima, further improving VG quality. Furthermore, our new VG representation supports conversion to standard XML-based SVG format, enhancing interoperability with existing VG tools and pipelines. Experimental results show that Bézier Splatting significantly outperforms existing methods with better visual fidelity and significant optimization speedup.
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引用它的顶会 Paper2
- 2D Gaussian Splatting for Bézier Spline Line Art VectorizationTianhao Chen, Clara Fernandez-Labrador, Marteinn Oskarsson, Chuck Tappan 等SIGGRAPH 2026
- DiffBMP: Differentiable Rendering with Bitmap PrimitivesSeongmin Hong, Junghun James Kim, Daehyeop Kim, Insoo Chung 等CVPR 2026
它引用的顶会 Paper23
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- Implicit Neural Representations with Periodic Activation FunctionsVincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman, David B. Lindell 等NeurIPS 2020 · 被引用 4,008 次
- DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content CreationJiaxiang Tang, Jiawei Ren, Hang Zhou, Ziwei Liu 等ICLR 2024 · 被引用 955 次
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