most citedDEGS: Deformable Event-based 3D Gaussian Splatting from RGB and Event Stream

3 citations · 4 across the 7 of their papers we have counts for

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cs.CV2025★ 3 cited

DEGS: Deformable Event-based 3D Gaussian Splatting from RGB and Event Stream

Junhao He, Jiaxu Wang, Jia Li +7

Reconstructing Dynamic 3D Gaussian Splatting (3DGS) from low-framerate RGB videos is challenging. This is because large inter-frame motions will increase the uncertainty of the sol…

cs.CV2024

DEL: Discrete Element Learner for Learning 3D Particle Dynamics with Neural Rendering

Jiaxu Wang, Jingkai Sun, Junhao He +4

Learning-based simulators show great potential for simulating particle dynamics when 3D groundtruth is available, but per-particle correspondences are not always accessible. The de…

cs.CV2024

PFGS: High Fidelity Point Cloud Rendering via Feature Splatting

Jiaxu Wang, Ziyi Zhang, Junhao He +1

Rendering high-fidelity images from sparse point clouds is still challenging. Existing learning-based approaches suffer from either hole artifacts, missing details, or expensive co…

cs.CV2024★ 1 cited

EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian Splatting

Jiaxu Wang, Junhao He, Ziyi Zhang +3

Event cameras offer promising advantages such as high dynamic range and low latency, making them well-suited for challenging lighting conditions and fast-moving scenarios. However,…

cs.CV2024

Learning Robust Generalizable Radiance Field with Visibility and Feature Augmented Point Representation

Jiaxu Wang, Ziyi Zhang, Renjing Xu

This paper introduces a novel paradigm for the generalizable neural radiance field (NeRF). Previous generic NeRF methods combine multiview stereo techniques with image-based neural…