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Recognizing object manipulation activities using depth and visual cues.

, , , and . J. Vis. Commun. Image Represent., 25 (4): 719-726 (2014)

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Recognizing object manipulation activities using depth and visual cues., , , and . J. Vis. Commun. Image Represent., 25 (4): 719-726 (2014)Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size., , , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 5731-5741. PMLR, (2021)A Scalable Approach to Activity Recognition based on Object Use., , , , and . ICCV, page 1-8. IEEE Computer Society, (2007)Energy proportional image sensors for continuous mobile vision., , , , and . MobiSys, page 467-468. ACM, (2013)Sensor-Based Understanding of Daily Life via Large-Scale Use of Common Sense., , , , and . AAAI, page 906-912. AAAI Press, (2006)Relational Learning for Collective Classification of Entities in Images., , and . StarAI@AAAI, volume WS-10-06 of AAAI Technical Report, AAAI, (2010)Structure Learning on Large Scale Common Sense Statistical Models of Human State., , and . AAAI, page 1389-1395. AAAI Press, (2008)Limiting Numerical Precision of Neural Networks to Achieve Real-Time Voice Activity Detection., , , , and . ICASSP, page 2236-2240. IEEE, (2018)Egocentric recognition of handled objects: Benchmark and analysis., and . CVPR Workshops, page 1-8. IEEE Computer Society, (2009)A Long-Term Evaluation of Sensing Modalities for Activity Recognition., , , , and . UbiComp, volume 4717 of Lecture Notes in Computer Science, page 483-500. Springer, (2007)