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We investigate privacy-preserving, video-based action recognition in deep learning, a problem with growing importance in smart camera applications.
T. U. S. D. of Justice, “Privacy act of 1974, as amended, 5 u.s.c. § 552a,” 1974. [Online]. Available: https://tinyurl.com/yb2u2s6g
1974
Earlier work this paper cites.
T. U. S. D. of Homeland Security, “Passenger name records agreements,” 2004. [Online]. Available: https://tinyurl.com/y4g2djf3
2004
Earlier work this paper cites.
A. Chattopadhyay and T. E. Boult, “Privacycam: a privacy preserving camera using uclinux on the blackfin dsp,” in CVPR , 2007
2007
Earlier work this paper cites.
C. Gentry et al. , “Fully homomorphic encryption using ideal lattices.” in STOC , 2009
2009
Earlier work this paper cites.
P. Weinzaepfel, H. Jégou, and P. Pérez, “Reconstructing an image from its local descriptors,” in CVPR , 2011
2011
Earlier work this paper cites.
H. Kuehne, H. Jhuang, E. Garrote, T. Poggio, and T. Serre, “Hmdb: a large video database for human motion recognition,” in ICCV , 2011
2011
Earlier work this paper cites.
S. Tao, M. Kudo, and H. Nonaka, “Privacy-preserved behavior analysis and fall detection by an infrared ceiling sensor network,” Sensors , 2012
2012
Earlier work this paper cites.
G. Desjardins, A. Courville, and Y. Bengio, “Disentangling factors of variation via generative entangling,” arXiv , 2012
2012
Earlier work this paper cites.
K. Soomro, A. R. Zamir, and M. Shah, “Ucf101: A dataset of 101 human actions classes from videos in the wild,” arXiv , 2012
2012
Earlier work this paper cites.
K. Yun, J. Honorio, D. Chattopadhyay, T. L. Berg, and D. Samaras, “Two-person interaction detection using body-pose features and multiple instance learning,” in CVPRW , 2012
2012
Earlier work this paper cites.
D.-Z. Du and P. M. Pardalos, Minimax and applications , 2013
2013
Earlier work this paper cites.
H. Kato and T. Harada, “Image reconstruction from bag-of-visual-words,” in CVPR , 2014
2014
Earlier work this paper cites.
P. Xie, M. Bilenko, T. Finley, R. Gilad-Bachrach, K. Lauter, and M. Naehrig, “Crypto-nets: Neural networks over encrypted data,” arXiv , 2014
2014
Earlier work this paper cites.
T. Winkler, A. Erdélyi, and B. Rinner, “Trusteye. m4: protecting the sensor—not the camera,” in AVSS , 2014
2014
Earlier work this paper cites.
L. Jia and R. J. Radke, “Using time-of-flight measurements for privacy-preserving tracking in a smart room,” IINF , 2014
2014
Earlier work this paper cites.
D. J. Butler, J. Huang, F. Roesner, and M. Cakmak, “The privacy-utility tradeoff for remotely teleoperated robots,” in HRI , 2015
2015
Earlier work this paper cites.
J. Dai, B. Saghafi, J. Wu, J. Konrad, and P. Ishwar, “Towards privacy-preserving recognition of human activities,” in ICIP , 2015
2015
Earlier work this paper cites.
F. Pittaluga and S. J. Koppal, “Privacy preserving optics for miniature vision sensors,” in CVPR , 2015
2015
Earlier work this paper cites.
Y. Ganin and V. Lempitsky, “Unsupervised domain adaptation by backpropagation,” in ICML , 2015
2015
Earlier work this paper cites.
D. Tran, L. Bourdev, R. Fergus, L. Torresani, and M. Paluri, “Learning spatiotemporal features with 3d convolutional networks,” in ICCV , 2015
2015
Earlier work this paper cites.
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, “Going deeper with convolutions,” in CVPR , 2015
2015
Earlier work this paper cites.
D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” in ICLR , 2015
2015
Earlier work this paper cites.
B. G. Fabian Caba Heilbron, Victor Escorcia and J. C. Niebles, “Activitynet: A large-scale video benchmark for human activity understanding,” in CVPR , 2015
2015
Earlier work this paper cites.
2015
Cited alongside, same era.
M. W. Tobias, “Is your smart security camera protecting your home or spying on you?” August 2016. [Online]. Available: https://tinyurl.com/y2yu7hc3
2016
Cited alongside, same era.
M. A. Weiss and K. Archick, “Us-eu data privacy: from safe harbor to privacy shield,” 2016
2016
Cited alongside, same era.
A. Dosovitskiy and T. Brox, “Inverting visual representations with convolutional networks,” in CVPR , 2016
2016
Cited alongside, same era.
A. Mahendran and A. Vedaldi, “Visualizing deep convolutional neural networks using natural pre-images,” IJCV , 2016
2016
Cited alongside, same era.
M. Xu, A. Sharghi, X. Chen, and D. J. Crandall, “Fully-coupled two-stream spatiotemporal networks for extremely low resolution action recognition,” in WACV , 2018
2018
Later among the works it cites.
B. H. Zhang, B. Lemoine, and M. Mitchell, “Mitigating unwanted biases with adversarial learning,” in AIES , 2018
2018
Later among the works it cites.
Z. Ren, Y. Jae Lee, and M. S. Ryoo, “Learning to anonymize faces for privacy preserving action detection,” in ECCV , 2018
2018
Later among the works it cites.
R. R. Shetty, M. Fritz, and B. Schiele, “Adversarial scene editing: Automatic object removal from weak supervision,” in NeurIPS , 2018
2018
Later among the works it cites.
W. Oleszkiewicz, P. Kairouz, K. Piczak, R. Rajagopal, and T. Trzciński, “Siamese generative adversarial privatizer for biometric data,” in ACCV , 2018
2018
Later among the works it cites.
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Z. Wang, S. Chang, Y. Yang, D. Liu, and T. S. Huang, “Studying very low resolution recognition using deep networks,” CVPR , 2016
2016
Cited alongside, same era.
S. J. Oh, R. Benenson, M. Fritz, and B. Schiele, “Faceless person recognition: Privacy implications in social media,” in ECCV , 2016
2016
Cited alongside, same era.
R. McPherson, R. Shokri, and V. Shmatikov, “Defeating image obfuscation with deep learning,” arXiv , 2016
2016
Cited alongside, same era.
S. Reddy, I. Labutov, S. Banerjee, and T. Joachims, “Unbounded human learning: Optimal scheduling for spaced repetition,” in SIGKDD , 2016
2016
Cited alongside, same era.
J. Johnson, A. Alahi, and L. Fei-Fei, “Perceptual losses for real-time style transfer and super-resolution,” in ECCV , 2016
2016
Cited alongside, same era.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” CVPR , 2016
2016
Cited alongside, same era.
K. He, X. Zhang, S. Ren, and J. Sun, “Identity mappings in deep residual networks,” in ECCV , 2016
2016
Cited alongside, same era.
J. Hamm and Y.-K. Noh, “K-beam minimax: Efficient optimization for deep adversarial learning,” in ICML , 2018
2018
Later among the works it cites.
X. Xiang and T. D. Tran, “Linear disentangled representation learning for facial actions,” TCSVT , 2018
2018
Later among the works it cites.
A. Gonzalez-Garcia, J. van de Weijer, and Y. Bengio, “Image-to-image translation for cross-domain disentanglement,” arXiv , 2018
2018
Later among the works it cites.
B. Zoph, V. Vasudevan, J. Shlens, and Q. V. Le, “Learning transferable architectures for scalable image recognition,” in CVPR , 2018
2018
Later among the works it cites.
M. Sandler, A. Howard, M. Zhu, A. Zhmoginov, and L.-C. Chen, “Mobilenetv2: Inverted residuals and linear bottlenecks,” in CVPR , 2018
2018
Later among the works it cites.
C. Gu, C. Sun, D. A. Ross, C. Vondrick, C. Pantofaru, Y. Li, S. Vijayanarasimhan, G. Toderici, S. Ricco, R. Sukthankar et al. , “Ava: A video dataset of spatio-temporally localized atomic visual actions,” in CVPR , 2018
2018
Later among the works it cites.
C. H. Donna Lu, “How abusers are exploiting smart home devices?” October 2019. [Online]. Available: https://tinyurl.com/y4moswga
2019
Closest in time.
D. Harwell, “Doorbell-camera firm ring has partnered with 400 police forces, extending surveillance concerns,” August 2019. [Online]. Available: https://tinyurl.com/szaxvxv
2019
Closest in time.
T. Brewster, “Thousands of banned chinese surveillance cameras are watching over america,” August 2019. [Online]. Available: https://tinyurl.com/y3vztmzf
2019
Closest in time.
F. Pittaluga, S. J. Koppal, S. B. Kang, and S. N. Sinha, “Revealing scenes by inverting structure from motion reconstructions,” in CVPR , 2019
2019
Closest in time.
Z. W. Wang, V. Vineet, F. Pittaluga, S. N. Sinha, O. Cossairt, and S. Bing Kang, “Privacy-preserving action recognition using coded aperture videos,” in CVPRW , 2019
2019
Closest in time.
Z. Wu, K. Suresh, P. Narayanan, H. Xu, H. Kwon, and Z. Wang, “Delving into robust object detection from unmanned aerial vehicles: A deep nuisance disentanglement approach,” in ICCV , 2019
2019
Closest in time.
P. M Uplavikar, Z. Wu, and Z. Wang, “All-in-one underwater image enhancement using domain-adversarial learning,” in CVPRW , 2019
2019
Closest in time.
F. Pittaluga, S. Koppal, and A. Chakrabarti, “Learning privacy preserving encodings through adversarial training,” in WACV , 2019
2019
Closest in time.
M. Bertran, N. Martinez, A. Papadaki, Q. Qiu, M. Rodrigues, G. Reeves, and G. Sapiro, “Adversarially learned representations for information obfuscation and inference,” in ICML , 2019
2019
Closest in time.
P. C. Roy and V. N. Boddeti, “Mitigating information leakage in image representations: A maximum entropy approach,” in CVPR , 2019
2019
Closest in time.
T. Wang, J. Zhao, M. Yatskar, K.-W. Chang, and V. Ordonez, “Balanced datasets are not enough: Estimating and mitigating gender bias in deep image representations,” in ICCV , 2019
2019
Closest in time.
D. Gurari, Q. Li, C. Lin, Y. Zhao, A. Guo, A. Stangl, and J. P. Bigham, “Vizwiz-priv: A dataset for recognizing the presence and purpose of private visual information in images taken by blind people,” in CVPR , 2019
2019
Closest in time.