3 citations · 4 across the 4 of their papers we have counts for
4 papers
Efficient Hybrid SE(3)-Equivariant Visuomotor Flow Policy via Spherical Harmonics for Robot Manipulation
Qinglun Zhang, Shen Cheng, Tian Dan +3
While existing equivariant methods enhance data efficiency, they suffer from high computational intensity, reliance on single-modality inputs, and instability when combined with fa…
FlowPolicy: Enabling Fast and Robust 3D Flow-based Policy via Consistency Flow Matching for Robot Manipulation
Qinglun Zhang, Zhen Liu, Haoqiang Fan +3
Robots can acquire complex manipulation skills by learning policies from expert demonstrations, which is often known as vision-based imitation learning. Generating policies based o…
PointRegGPT: Boosting 3D Point Cloud Registration using Generative Point-Cloud Pairs for Training
Suyi Chen, Hao Xu, Haipeng Li +5
Data plays a crucial role in training learning-based methods for 3D point cloud registration. However, the real-world dataset is expensive to build, while rendering-based synthetic…
SpectralNeRF: Physically Based Spectral Rendering with Neural Radiance Field
Ru Li, Jia Liu, Guanghui Liu +3
In this paper, we propose SpectralNeRF, an end-to-end Neural Radiance Field (NeRF)-based architecture for high-quality physically based rendering from a novel spectral perspective.…