High-efficiency 3D Gaussian splatting rendering assisted by event signal sampling

3D Gaussian Splatting has marked a significant milestone in novel view synthesis, particularly in the real-time level rendering speed. Despite its remarkable contributions, this technique encounters substantial challenges when reconstructing dynamic scenes due to motion blur, which leads to inaccurate point clouds and low-resolution vision performance. To address this issue, this paper proposes an event camera assisting 3D Gaussian Splatting generation, which provides high-accuracy vision cues for reliable motion description. Because moving objects attract more attention, the entire scene is rendered at different precision scales. Specifically, the proposed solution provides a detailed rendering of the space captured by the event camera and reduces its rendering accuracy for static backgrounds. Our comparative experiments demonstrate that the adoption of event camera imagery significantly improves the fidelity of the novel view synthesis, thereby enhancing the overall reconstruction quality in dynamic scenes.