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ClusterVO: Clustering Moving Instances and Estimating Visual Odometry for Self and Surroundings
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
We present ClusterVO, a stereo Visual Odometry which simultaneously clusters and estimates the motion of both ego and surrounding rigid clusters/objects. Unlike previous solutions relying on batch input or imposing priors on scene structure or dynamic object models, ClusterVO is online, general and thus can be used in various scenarios including indoor scene understanding and autonomous driving. At the core of our system lies a multi-level probabilistic association mechanism and a heterogeneous
doi:10.1109/cvpr42600.2020.00224
dblp:conf/cvpr/HuangYM020
fatcat:6n5augbfzjfzrp7y2qlxci62xq