Analysis of the 3D LiDAR point cloud data is the fundamental for computer vision and robotics, with potential applications ranging from object detection to scene understanding. In this proposed work, introduced an approach that leverages the power of contrastive learning combined with self-supervise
Jisheng YangZijun HuangMaochun HuangXianxian ZengDong LiYun Zhang
Zhongyang ZhaoYinglei ChengXiaosong ShiXianxiang Qin
Congcong WenLina YangLi XiangLing PengTianhe Chi
Abhith KrishnaSainath BitraguntaAnanthakrishna Chintanpalli
Bocun LiuSijie ChangHaotian LinJing Jiang