HKU engineering research team led by Prof. Edmund Y. Lam from the HKU Department of Electrical and Electronic Engineering has won the Best Paper Award (Third Place) for their paper titled “Ev-GS: Event-based Gaussian Splatting for Efficient and Accurate Radiance Field Rendering” (https://arxiv.org/abs/2407.11343) at the IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2024 (IEEE MLSP 2024), held in London, UK.
In their work, the team proposed the first CNI-informed scheme to infer 3D Gaussian splatting from a monocular event camera, enabling efficient novel view synthesis. Leveraging 3D Gaussians with pure event-based supervision, Ev-GS overcomes challenges such as the detection of fast-moving objects and insufficient lighting. Experimental results show that Ev-GS outperforms the method that takes frame-based signals as input by rendering realistic views with reduced blurring and improved visual quality. Moreover, it demonstrates competitive reconstruction quality and reduced computing occupancy compared to existing methods, which paves the way to a highly efficient CNI approach for signal processing.