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

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

collaborators

7 papers

cs.CV20253 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.RO2024

Query-based Semantic Gaussian Field for Scene Representation in Reinforcement Learning

Jiaxu Wang, Ziyi Zhang, Qiang Zhang +5

Latent scene representation plays a significant role in training reinforcement learning (RL) agents. To obtain good latent vectors describing the scenes, recent works incorporate t…

cs.CV2024

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.RO2024

Physical Priors Augmented Event-Based 3D Reconstruction

Jiaxu Wang, Junhao He, Ziyi Zhang +1

3D neural implicit representations play a significant component in many robotic applications. However, reconstructing neural radiance fields (NeRF) from realistic event data remain…