SweepEvGS: Event-Based 3D Gaussian Splatting for Macro and Micro Radiance Field Rendering From a Single Sweep
Recent advancements in 3D Gaussian Splatting (3D-GS) have demonstrated the potential of using 3D Gaussian primitives for high-speed, high-fidelity, and cost-efficient novel view synthesis from continuously calibrated input views. However, conventional methods require high-frame-rate dense and high-quality sharp images, which are time-consuming and inefficient to capture, especially in dynamic environments. Event cameras, with their high temporal resolution and ability to capture asynchronous brightness changes, offer a promising alternative for more reliable scene reconstruction without motion blur. In this paper, we propose SweepEvGS, a novel hardware-integrated method that leverages event cameras for robust and accurate novel view synthesis across various imaging settings from a single sweep. SweepEvGS utilizes the initial static frame with dense event streams captured during a single camera sweep to effectively reconstruct detailed scene views. We also introduce different real-world hardware imaging systems for real-world data collection and evaluation for future research. We validate the robustness and efficiency of SweepEvGS through experiments in three different imaging settings: synthetic objects, real-world macro-level, and real-world micro-level view synthesis. Our results demonstrate that SweepEvGS surpasses existing methods in visual rendering quality, rendering speed, and computational efficiency, highlighting its potential for dynamic practical applications.
Authors
- Edmund Y. M. Lam (ORCID: https://orcid.org/0000-0001-6268-950X)
- Shuo Zhu (ORCID: https://orcid.org/0000-0002-3000-1536)
- Chutian Wang (ORCID: https://orcid.org/0000-0002-5941-8028)
- Boxin Shi (ORCID: https://orcid.org/0000-0001-6749-0364)
- Jingqian Wu
Institutions
- Peking University (CN)
- University of Hong Kong (HK)
Publication Details
- Journal
- IEEE Transactions on Circuits and Systems for Video Technology
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1109/tcsvt.2025.3583735
- Citations
- 1
- Primary Topic
- Computer Graphics and Visualization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 3.54