SpikeGS: Reconstruct 3D scene via fast-moving bio-inspired sensors

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View a PDF of the paper titled SpikeGS: Reconstruct 3D scene via fast-moving bio-inspired sensors, by Yijia Guo and 4 other authors

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Abstract:3D Gaussian Splatting (3DGS) demonstrates unparalleled superior performance in 3D scene reconstruction. However, 3DGS heavily relies on the sharp images. Fulfilling this requirement can be challenging in real-world scenarios especially when the camera moves fast, which severely limits the application of 3DGS. To address these challenges, we proposed Spike Gausian Splatting (SpikeGS), the first framework that integrates the spike streams into 3DGS pipeline to reconstruct 3D scenes via a fast-moving bio-inspired camera. With accumulation rasterization, interval supervision, and a specially designed pipeline, SpikeGS extracts detailed geometry and texture from high temporal resolution but texture lacking spike stream, reconstructs 3D scenes captured in 1 second. Extensive experiments on multiple synthetic and real-world datasets demonstrate the superiority of SpikeGS compared with existing spike-based and deblur 3D scene reconstruction methods. Codes and data will be released soon.

Submission history

From: Liwen Hu [view email]
[v1]
Thu, 4 Jul 2024 09:32:12 UTC (15,806 KB)
[v2]
Mon, 26 Aug 2024 16:15:57 UTC (17,182 KB)
[v3]
Wed, 11 Dec 2024 15:52:12 UTC (22,391 KB)



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