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@incollection{winkler2001vision,
title={Vision and video: models and applications},
author={Winkler, Stefan and Kunt, Murat and van den Branden Lambrecht, Christian J},
booktitle={Vision Models and Applications to Image and Video Processing},
pages={201--229},
year={2001},
publisher={Springer}
}
@article{wallace1992jpeg,
title={The JPEG still picture compression standard},
author={Wallace, Gregory K},
journal={IEEE transactions on consumer electronics},
volume={38},
number={1},
pages={xviii--xxxiv},
year={1992},
publisher={IEEE}
}
@inproceedings{smith1994fast,
title={Fast software processing of motion JPEG video},
author={Smith, B},
booktitle={Proceedings of the second ACM international conference on Multimedia},
pages={77--88},
year={1994},
organization={ACM}
}
@inproceedings{chang1992video,
title={Video Compositing in the DCT domain},
author={Chang, S-F},
booktitle={IEEE Workshop on Visual Signal Processing and Communications, Raleigh, NC, Sep. 1992},
year={1992}
}
@inproceedings{shen1995inner,
title={Inner-block operations on compressed images},
author={Shen, Bo and Sethi, Ishwar K},
booktitle={Proceedings of the third ACM international conference on Multimedia},
pages={489--498},
year={1995},
organization={ACM}
}
@inproceedings{natarajan1995fast,
title={A fast approximate algorithm for scaling down digital images in the DCT domain},
author={Natarajan, Balas K and Vasudev, Bhaskaran},
booktitle={Image Processing, 1995. Proceedings., International Conference on},
volume={2},
pages={241--243},
year={1995},
organization={IEEE}
}
@article{smith1993algorithms,
title={Algorithms for manipulating compressed images},
author={Smith, Brian C and Rowe, Lawrence A},
journal={IEEE Computer Graphics and Applications},
volume={13},
number={5},
pages={34--42},
year={1993},
publisher={IEEE}
}
@inproceedings{shen1996direct,
title={Direct feature extraction from compressed images},
author={Shen, Bo and Sethi, Ishwar K},
booktitle={Storage and Retrieval for Still Image and Video Databases IV},
volume={2670},
pages={404--415},
year={1996},
organization={International Society for Optics and Photonics}
}
@inproceedings{chang1993new,
title={A new approach to decoding and compositing motion-compensated DCT-based images},
author={Chang, Shih-Fu and Messerschmitt, David G},
booktitle={icassp},
pages={421--424vol},
year={1993},
organization={IEEE}
}
@article{shen1998block,
title={Block-based manipulations on transform-compressed images and videos},
author={Shen, Bo and Sethi, Ishwar K},
journal={Multimedia Systems},
volume={6},
number={2},
pages={113--124},
year={1998},
publisher={Springer}
}
@article{ioffe2015batch,
title={Batch normalization: Accelerating deep network training by reducing internal covariate shift},
author={Ioffe, Sergey and Szegedy, Christian},
journal={arXiv preprint arXiv:1502.03167},
year={2015}
}
@inproceedings{he2016deep,
title={Deep residual learning for image recognition},
author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={770--778},
year={2016}
}
@inproceedings{paszke2017automatic,
title={Automatic differentiation in PyTorch},
author={Paszke, Adam and Gross, Sam and Chintala, Soumith and Chanan, Gregory and Yang, Edward and DeVito, Zachary and Lin, Zeming and Desmaison, Alban and Antiga, Luca and Lerer, Adam},
booktitle={NIPS-W},
year={2017}
}
@misc{tensorflow2015-whitepaper,
title={{TensorFlow}: Large-Scale Machine Learning on Heterogeneous Systems},
url={http://tensorflow.org/},
note={Software available from tensorflow.org},
author={
Mart\'{\i}n~Abadi and
Ashish~Agarwal and
Paul~Barham and
Eugene~Brevdo and
Zhifeng~Chen and
Craig~Citro and
Greg~S.~Corrado and
Andy~Davis and
Jeffrey~Dean and
Matthieu~Devin and
Sanjay~Ghemawat and
Ian~Goodfellow and
Andrew~Harp and
Geoffrey~Irving and
Michael~Isard and
Yangqing Jia and
Rafal~Jozefowicz and
Lukasz~Kaiser and
Manjunath~Kudlur and
Josh~Levenberg and
Dan~Man\'{e} and
Rajat~Monga and
Sherry~Moore and
Derek~Murray and
Chris~Olah and
Mike~Schuster and
Jonathon~Shlens and
Benoit~Steiner and
Ilya~Sutskever and
Kunal~Talwar and
Paul~Tucker and
Vincent~Vanhoucke and
Vijay~Vasudevan and
Fernanda~Vi\'{e}gas and
Oriol~Vinyals and
Pete~Warden and
Martin~Wattenberg and
Martin~Wicke and
Yuan~Yu and
Xiaoqiang~Zheng},
year={2015},
}
@article{jia2014caffe,
Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
Journal = {arXiv preprint arXiv:1408.5093},
Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
Year = {2014}
}
@article{chetlur2014cudnn,
title={cudnn: Efficient primitives for deep learning},
author={Chetlur, Sharan and Woolley, Cliff and Vandermersch, Philippe and Cohen, Jonathan and Tran, John and Catanzaro, Bryan and Shelhamer, Evan},
journal={arXiv preprint arXiv:1410.0759},
year={2014}
}
@inproceedings{wu2018compressed,
title={Compressed video action recognition},
author={Wu, Chao-Yuan and Zaheer, Manzil and Hu, Hexiang and Manmatha, R and Smola, Alexander J and Kr{\"a}henb{\"u}hl, Philipp},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
pages={6026--6035},
year={2018}
}
@inproceedings{gueguen_2018_ICLR,
title={Faster Neural Networks Straight from JPEG},
author={Lionel Gueguen and Alex Sergeev and Ben Kadlec and Rosanne Liu and Jason Yosinski},
booktitle={International Conference on Learning Representations},
year={2018}
}
@inproceedings{arman1993image,
title={Image processing on compressed data for large video databases},
author={Arman, Farshid and Hsu, Arding and Chiu, Ming-Yee},
booktitle={Proceedings of the first ACM international conference on Multimedia},
pages={267--272},
year={1993},
organization={ACM}
}
@inproceedings{he2009efficient,
title={Efficient image retrieval in DCT domain by hypothesis testing},
author={He, Daan and Gu, Zhenmei and Cercone, Nick},
booktitle={Image Processing (ICIP), 2009 16th IEEE International Conference on},
pages={225--228},
year={2009},
organization={IEEE}
}
@inproceedings{feng2002jpeg,
title={JPEG image retrieval based on features from DCT domain},
author={Feng, Guocan and Jiang, Jianmin},
booktitle={International Conference on Image and Video Retrieval},
pages={120--128},
year={2002},
organization={Springer}
}
@inproceedings{ghosh2016deep,
title={Deep feature extraction in the DCT domain},
author={Ghosh, Arthita and Chellappa, Rama},
booktitle={Pattern Recognition (ICPR), 2016 23rd International Conference on},
pages={3536--3541},
year={2016},
organization={IEEE}
}
@inproceedings{wu2013sift,
title={SIFT Feature Extraction Algorithm for Image in DCT Domain},
author={Wu, Zhen and Xu, Zhe and Zhang, Rui Nian and Li, Shao Mei},
booktitle={Applied Mechanics and Materials},
volume={347},
pages={2963--2967},
year={2013},
organization={Trans Tech Publ}
}
@article{lecun1998mnist,
title={The MNIST database of handwritten digits},
author={LeCun, Yann},
journal={http://yann. lecun. com/exdb/mnist/}
}
@techreport{krizhevsky2009learning,
title={Learning multiple layers of features from tiny images},
author={Krizhevsky, Alex and Hinton, Geoffrey},
year={2009},
institution={Citeseer}
}
@inproceedings{ronneberger2015u,
title={U-net: Convolutional networks for biomedical image segmentation},
author={Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
booktitle={International Conference on Medical image computing and computer-assisted intervention},
pages={234--241},
year={2015},
organization={Springer}
}
@inproceedings{krizhevsky2012imagenet,
title={Imagenet classification with deep convolutional neural networks},
author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
booktitle={Advances in neural information processing systems},
pages={1097--1105},
year={2012}
}
@article{najafabadi2015deep,
title={Deep learning applications and challenges in big data analytics},
author={Najafabadi, Maryam M and Villanustre, Flavio and Khoshgoftaar, Taghi M and Seliya, Naeem and Wald, Randall and Muharemagic, Edin},
journal={Journal of Big Data},
volume={2},
number={1},
pages={1},
year={2015},
publisher={Springer}
}
@article{han2015deep,
title={Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding},
author={Han, Song and Mao, Huizi and Dally, William J},
journal={arXiv preprint arXiv:1510.00149},
year={2015}
}
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\input{sections/introduction}
\input{sections/priorwork}
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\input{sections/jdr}
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\input{sections/conclusion}
{\small
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,MNIST,CIFAR10,CIFAR100
Average Spatial Accuracy,0.9881829999999998,0.7253580000000001,
Average JPEG Accuracy,0.9881859999999998,0.7253489999999999,
Deviation,2.9999999999752447e-06,9.000000000147779e-06,
\title{Deep Residual Learning in the JPEG Transform Domain}
\author{Max Ehrlich and Larry Davis\\
{\tt\small maxehr@umiacs.umd.edu} \qquad {\tt\small lsd@umiacs.umd.edu}\\
University of Maryland, College Park, MD, USA.
}
\maketitle
\begin{abstract}
We introduce a general method of performing Residual Network inference and learning in the JPEG transform domain that allows the network to consume compressed images as input. Our formulation leverages the linearity of the JPEG transform to redefine convolution and batch normalization with a tune-able numerical approximation for ReLu. The result is mathematically equivalent to the spatial domain network up to the ReLu approximation accuracy. A formulation for image classification and a model conversion algorithm for spatial domain networks are given as examples of the method. We show that the sparsity of the JPEG format allows for faster processing of the images with little to no penalty in the network accuracy.
\end{abstract}
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