WebSelf-Supervised Pillar Motion Learning for Autonomous Driving. Autonomous driving can benefit from motion behavior comprehension when interacting with diverse traffic participants in highly dynamic environments. Recently, there has been a growing interest in estimating class-agnostic motion directly from point clouds. WebarXiv.org e-Print archive
PillarMotion: Self-Supervised Pillar Motion Learning for …
Webfurther explores self-supervised learning of amodal 3D fea-ture representations agnostic to object and scene semantic content. The above methods focus on indoor RGB-D data. As for outdoor LIDAR point clouds, Pillar-Motion (Luo, Yang, and Yuille 2024) propose a self-supervised pillar rep-resentation learning method that makes use of the optical WebAmong the three kinds of self-supervised signal, spatial supervision can be derived from the structures in the static frame, spatio-temporal supervision naturally reflects the correlation across the different frames, and sequential supervision signifies the temporal coherence. short brown leather boots for women
Chenxu Luo - Google Scholar
Webtl;dr: Self-supervised pillar motion learning. Overall impression This paper is benchmarked against MotionNet. The backbone follows that of MotionNet, but instead of using bbox as … WebMar 31, 2024 · Abstract: In this study, we propose a novel pretext task and a self-supervised motion perception (SMP) method for spatiotemporal representation learning. The pretext … WebMar 16, 2024 · “Self-supervised learning for facial action unit recognition through temporal consistency,” in Proceedings of the British Machine Vision Conference (BMVC) (BMVA Press: ). [Google Scholar] Luo C., Yang X., Yuille A. (2024). “Self-supervised pillar motion learning for autonomous driving, ... sandy court house fivem