CMU-Flownet: Exploring Point Cloud Scene Flow Estimation in Occluded Scenario

no code implementations • 16 Apr 2024 • Jingze Chen, Junfeng Yao, Qiqin Lin, Lei LI

Occlusions hinder point cloud frame alignment in LiDAR data, a challenge inadequately addressed by scene flow models tested mainly on occlusion-free datasets.

Occlusion Estimation Occlusion Handling +1

DRSM: efficient neural 4d decomposition for dynamic reconstruction in stationary monocular cameras

no code implementations • 1 Feb 2024 • Weixing Xie, Xiao Dong, Yong Yang, Qiqin Lin, Jingze Chen, Junfeng Yao, Xiaohu Guo

With the popularity of monocular videos generated by video sharing and live broadcasting applications, reconstructing and editing dynamic scenes in stationary monocular cameras has become a special but anticipated technology.

Dynamic Reconstruction Neural Rendering

SSFlowNet: Semi-supervised Scene Flow Estimation On Point Clouds With Pseudo Label

no code implementations • 23 Dec 2023 • Jingze Chen, Junfeng Yao, Qiqin Lin, Rongzhou Zhou, Lei LI

This paper introduces SSFlowNet, a semi-supervised approach for scene flow estimation, that utilizes a blend of labeled and unlabeled data, optimizing the balance between the cost of labeling and the precision of model training.

Pseudo Label Scene Flow Estimation