This work introduces FastEventDGS, a novel Deformable Gaussian Splatting-based framework that leverages a single event camera for high-fidelity 4D reconstruction in dynamic scenes and proposes a local patch event motion loss to constrain object motion, effectively mitigating over-fitting.
This paper presents EvTrajGS, an accurate and efficient 3D Gaussian Splatting framework for unposed event streams that enables reliable joint pose-scene optimization initialized from coarse pose priors, eliminating the need for computationally expensive SLAM-style pipelines.
Zixuan Chen, Jiakai Zhang, Junhao Dong et al.· 0 citations
An event-RGB fusion Gaussian splatting framework that integrates event information into both optimization and densification stages of the Gaussian splatting pipeline, taking advantage of novel event sensors with high frame-rate.
Xiao-Yang Bai, Zhen-Yang Li, Wei-Wei Xu et al.· 0 citations
This paper proposes a framework for efficient incremental optimization of 3D Gaussian Splatting models and achieves a 24% relative improvement in SSIM with just 120 seconds of additional optimization on the Mip-NeRF360 dataset.
This work proposes a novel 3D-aware video restoration framework designed to enhance the quality of sparse 3DGS reconstruction and introduces a camera-conditioned geometric prior that guides the network toward geometrically grounded restoration that remains coherent across viewpoints.
Xinhui Liu, Can Wang, Wei Jiang et al.· 1 citation
This work fundamentally reimagines motion blur handling through a paradigm shift: rather than removing blur artifacts, the challenge is reformulate the challenge as a well-constrained forward problem that generatively models blur formation within the rendering pipeline.
This work introduces a novel prior-guided, multi-stage reconstruction pipeline that fuses geometric and motion priors to build a physically plausible and temporally stable foundation, and applies a universal trajectory-preserving technique, which safeguards high-quality motion by decoupling the appearance optimization...
Xiaosheng He, Feng-Lin Liu, Lin Gao et al.· IEEE Transactions on Visuali...· 0 citations
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