activity
20202023
most citedHierarchical Attention Learning of Scene Flow in 3D Point Clouds

74 citations · 181 across the 19 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CV2023★ 1 cited

RLSAC: Reinforcement Learning enhanced Sample Consensus for End-to-End Robust Estimation

Chang Nie, Guangming Wang, Zhe Liu +3

Robust estimation is a crucial and still challenging task, which involves estimating model parameters in noisy environments. Although conventional sampling consensus-based algorith…

cs.CV2023★ 2 cited

DELFlow: Dense Efficient Learning of Scene Flow for Large-Scale Point Clouds

Chensheng Peng, Guangming Wang, Xian Wan Lo +5

Point clouds are naturally sparse, while image pixels are dense. The inconsistency limits feature fusion from both modalities for point-wise scene flow estimation. Previous methods…

cs.RO2023★ 3 cited

End-to-end 2D-3D Registration between Image and LiDAR Point Cloud for Vehicle Localization

Guangming Wang, Yu Zheng, Yuxuan Wu +5

Robot localization using a built map is essential for a variety of tasks including accurate navigation and mobile manipulation. A popular approach to robot localization is based on…

cs.RO2023

Efficient Robot Skill Learning with Imitation from a Single Video for Contact-Rich Fabric Manipulation

Shengzeng Huo, Anqing Duan, Lijun Han +3

Classical policy search algorithms for robotics typically require performing extensive explorations, which are time-consuming and expensive to implement with real physical platform…

cs.CV2023★ 1 cited

RegFormer: An Efficient Projection-Aware Transformer Network for Large-Scale Point Cloud Registration

Jiuming Liu, Guangming Wang, Zhe Liu +3

Although point cloud registration has achieved remarkable advances in object-level and indoor scenes, large-scale registration methods are rarely explored. Challenges mainly arise…