Liquid Pouring Monitoring via Rich Sensory Inputs

Author:

Wu Tz-Ying,Lin Juan-Ting,Wang Tsun-Hsuang,Hu Chan-Wei,Niebles Juan Carlos,Sun Min

Publisher

Springer International Publishing

Reference45 articles.

1. Kubricht, J., Jiang, C., Zhu, Y., Zhu, S.C., Terzopoulos, D., Lu, H.: Probabilistic simulation predicts human performance on viscous fluid-pouring problem. In: CogSci (2016)

2. Bates, C.J., Yildirim, I., Tenenbaum, J.B., Battaglia, P.W.: Humans predict liquid dynamics using probabilistic simulation. In: CogSci (2015)

3. Edmonds, M., et al.: Feeling the force: integrating force and pose for fluent discovery through imitation learning to open medicine bottles. In: IROS (2017)

4. Abu-El-Haija, S., et al.: Youtube-8m: a large-scale video classification benchmark. arXiv:1609.08675 (2016)

5. Heilbron, F.C., Escorcia, V., Ghanem, B., Niebles, J.C.: Activitynet: a large-scale video benchmark for human activity understanding. In: CVPR (2015)

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Look and Listen: A Multi-Sensory Pouring Network and Dataset for Granular Media from Human Demonstrations;2022 International Conference on Robotics and Automation (ICRA);2022-05-23

2. Robust Robotic Pouring using Audition and Haptics;2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS);2020-10-24

3. Computer Vision for Recognition of Materials and Vessels in Chemistry Lab Settings and the Vector-LabPics Data Set;ACS Central Science;2020-09-10

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