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Recent advances in neural networks (NNs) have enabled automatic querying of large volumes of video data with high accuracy.
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D. Kang, J. Emmons, F. Abuzaid, P. Bailis, and M. Zaharia · 2017
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J. Redmon and A. Farhadi · 2017
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Fast video classification via adaptive cascading of deep models
H. Shen, S. Han, M. Philipose, and A. Krishnamurthy · 2017
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X. Zhu, Y. Wang, J. Dai, L. Yuan, and Y. Wei · 2017
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C. Coleman, D. Kang, D. Narayanan, L. Nardi, T. Zhao, J. Zhang, P. Bailis, K. Olukotun, C. Re, and M. Zaharia · 2018
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Detectron
R. Girshick, I. Radosavovic, G. Gkioxari, P. Dollár, and K. He · 2018
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Focus: Querying large video datasets with low latency and low cost
K. Hsieh, G. Ananthanarayanan, P. Bodik, P. Bahl, M. Philipose, P. B. Gibbons, and O. Mutlu · 2018
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Chameleon: scalable adaptation of video analytics
J. Jiang, G. Ananthanarayanan, P. Bodik, S. Sen, and I. Stoica · 2018
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Accelerating machine learning inference with probabilistic predicates
Y. Lu, A. Chowdhery, S. Kandula, and S. Chaudhuri · 2018
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Scanner: Efficient video analysis at scale (to appear)
A. Poms, W. Crichton, P. Hanrahan, and K. Fatahalian · 2018
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Predicate optimization for a visual analytics database
M. R. Anderson, M. Cafarella, T. F. Wenisch, and G. Ros · 2019
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Scaling video analytics on constrained edge nodes
C. Canel, T. Kim, G. Zhou, C. Li, H. Lim, D. Andersen, M. Kaminsky, and S. Dulloor · 2019
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Challenges and opportunities in dnn-based video analytics: A demonstration of the blazeit video query engine
D. Kang, P. Bailis, and M. Zaharia · 2019
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Optimizing declarative aggregation and limit queries for neural network-based video analytics
D. Kang, P. Bailis, and M. Zaharia · 2019
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Vstore: A data store for analytics on large videos
T. Xu, L. M. Botelho, and F. X. Lin · 2019
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