5.5.1 Learning, Neural Nets for Coding, Compression Video

Chapter Contents (Back)
Compression. Neural Nets. Learning.

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Zhang, C., He, X.,
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CirSysVideo(23), No. 4, April 2013, pp. 565-576.
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CirSysVideo(24), No. 10, October 2014, pp. 1743-1757.
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Earlier: A1, A3, A4, Only:
Sparse representation of texture patches for low bit-rate image compression,
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Damerchilu, B.[Bahman], Norouzzadeh, M.S.[Mohammad Sadegh], Meybodi, M.R.[Mohammad Reza],
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Springer DOI 1610
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Elsevier DOI 1609
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Earlier: A2, A1, A3, A4:
Image Saliency Detection with Sparse Representation of Learnt Texture Atoms,
RSL-CV15(894-902)
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Visual attention Databases BibRef

Xu, M.[Mai], Jiang, L.[Lai], Sun, X., Ye, Z.T.[Zhao-Ting], Wang, Z.[Zulin],
Learning to Detect Video Saliency With HEVC Features,
IP(26), No. 1, January 2017, pp. 369-385.
IEEE DOI 1612
computer vision BibRef

Sun, Y.P.[Yi-Peng], Tao, X.M.[Xiao-Ming], Li, Y.[Yang], Lu, J.H.[Jian-Hua],
Dictionary Learning for Image Coding Based on Multisample Sparse Representation,
CirSysVideo(24), No. 11, November 2014, pp. 2004-2010.
IEEE DOI 1411
compressed sensing BibRef

Chen, Z., He, T., Jin, X., Wu, F.,
Learning for Video Compression,
CirSysVideo(30), No. 2, February 2020, pp. 566-576.
IEEE DOI 2002
Image coding, Video compression, Spatiotemporal phenomena, Image reconstruction, Transform coding, Codecs, Video coding, PixelMotionCNN BibRef

Ma, L.[Lin], Zhao, D.B.[De-Bin], Gao, W.[Wen],
Learning-based image restoration for compressed images,
SP:IC(27), No. 1, January 2012, pp. 54-65.
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Image restoration; Compression artifacts; Primitive BibRef

Liu, X.M.[Xian-Ming], Cheung, G.[Gene], Wu, X.L.[Xiao-Lin], Zhao, D.B.[De-Bin],
Random Walk Graph Laplacian-Based Smoothness Prior for Soft Decoding of JPEG Images,
IP(26), No. 2, February 2017, pp. 509-524.
IEEE DOI 1702
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Earlier:
Inter-block consistent soft decoding of JPEG images with sparsity and graph-signal smoothness priors,
ICIP15(1628-1632)
IEEE DOI 1512
Laplace equations. graph signal processing; image decoding; sparse signal representation BibRef

Liu, X.M.[Xian-Ming], Wu, X.L.[Xiao-Lin], Zhou, J.T.[Jian-Tao], Zhao, D.B.[De-Bin],
Data-driven sparsity-based restoration of JPEG-compressed images in dual transform-pixel domain,
CVPR15(5171-5178)
IEEE DOI 1510
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Liu, X.M.[Xian-Ming], Wu, X.L.[Xiao-Lin], Zhao, D.B.[De-Bin],
Sparsity-based soft decoding of compressed images in transform domain,
ICIP13(563-566)
IEEE DOI 1402
Decoding. Restore compressed images not decoded images. BibRef

Yeh, C.H.[Chia-Hung], Kang, L.W.[Li-Wei], Chiou, Y.W.[Yi-Wen], Lin, C.W.[Chia-Wen], Jiang, S.J.F.[Shu-Jhen Fan],
Self-learning-based post-processing for image/video deblocking via sparse representation,
JVCIR(25), No. 5, 2014, pp. 891-903.
Elsevier DOI 1406
BibRef
Earlier: A3, A1, A2, A4, A5:
Efficient image/video deblocking via sparse representation,
VCIP12(1-6).
IEEE DOI 1302
Blocking artifact BibRef

Kang, L.W., Hsu, C.C., Zhuang, B., Lin, C.W., Yeh, C.H.,
Learning-Based Joint Super-Resolution and Deblocking for a Highly Compressed Image,
MultMed(17), No. 7, July 2015, pp. 921-934.
IEEE DOI 1506
Dictionaries BibRef

Zhang, B.C.[Bao-Chang], Gu, J.X.[Jia-Xin], Chen, C.[Chen], Han, J.G.[Jun-Gong], Su, X.B.[Xiang-Bo], Cao, X.B.[Xian-Bin], Liu, J.Z.[Jian-Zhuang],
One-two-one networks for compression artifacts reduction in remote sensing,
PandRS(145), 2018, pp. 184-196.
Elsevier DOI 1810
Compression artifacts reduction, Remote sensing, Deep learning, One-two-one network BibRef

Gan, Z.L.[Zong-Liang],
Low Bit-Rate Compression Image Restoration through Subspace Joint Regression Learning,
IEICE(E101-D), No. 10, October 2018, pp. 2539-2542.
WWW Link. 1810
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Wang, M., Xie, W., Meng, X., Zeng, H., Ngan, K.N.,
UHD Video Coding: A Light-Weight Learning-Based Fast Super-Block Approach,
CirSysVideo(29), No. 10, October 2019, pp. 3083-3094.
IEEE DOI 1910
data compression, high definition video, image colour analysis, image resolution, image texture, video coding, medium coding unit, HEVC BibRef

Zhao, L.J.[Li-Jun], Bai, H.H.[Hui-Hui], Wang, A.H.[An-Hong], Zhao, Y.[Yao],
Learning a virtual codec based on deep convolutional neural network to compress image,
JVCIR(63), 2019, pp. 102589.
Elsevier DOI 1909
Image representation, Image compression, Soft-projection, Virtual codec, Post-processing BibRef

Yu, L.W.[Liang-Wei], Shen, L.Q.[Li-Quan], Yang, H.[Hao], Wang, L.[Lu], An, P.[Ping],
Quality Enhancement Network via Multi-Reconstruction Recursive Residual Learning for Video Coding,
SPLetters(26), No. 4, April 2019, pp. 557-561.
IEEE DOI 1903
Image reconstruction, Feature extraction, Training, Image coding, Encoding, Periodic structures, Compression algorithms, quality enhancement BibRef

Liu, Y.[Ying], Tountas, K.[Konstantinos], Pados, D.A.[Dimitris A.], Batalama, S.N.[Stella N.], Medley, M.J.[Michael J.],
L1-Subspace Tracking for Streaming Data,
PR(97), 2020, pp. 106992.
Elsevier DOI 1910
Dimensionality reduction, Eigenvector decomposition, Internet-of-Things, -norm, Outliers, Subspace learning BibRef

Fu, H.S.[Hai-Sheng], Liang, F.[Feng], Lei, B.[Bo], Bian, N.[Nai], Zhang, Q.[Qian], Akbari, M.[Mohammad], Liang, J.[Jie], Tu, C.J.[Cheng-Jie],
Improved hybrid layered image compression using deep learning and traditional codecs,
SP:IC(82), 2020, pp. 115774.
Elsevier DOI 2001
Deep learning-based image coding, Layered image coding, Residual coding, Convolutional neural network, Autoencoder BibRef

Song, Q., Xiong, R., Fan, X., Liu, D., Wu, F., Huang, T., Gao, W.,
Compressed Image Restoration via Artifacts-Free PCA Basis Learning and Adaptive Sparse Modeling,
IP(29), 2020, pp. 7399-7413.
IEEE DOI 2007
Compressed image restoration, sparse modeling, paired PCA learning, adaptive distribution modeling BibRef

Liu, J., Liu, D., Yang, W., Xia, S., Zhang, X., Dai, Y.,
A Comprehensive Benchmark for Single Image Compression Artifact Reduction,
IP(29), 2020, pp. 7845-7860.
IEEE DOI 2007
Compression artifacts removal, benchmark, side information, loop filter, deep learning BibRef

Cheng, Z., Sun, H., Takeuchi, M., Katto, J.,
Energy Compaction-Based Image Compression Using Convolutional AutoEncoder,
MultMed(22), No. 4, April 2020, pp. 860-873.
IEEE DOI 2004
Image compression, convolutional autoencoder, optimum bit allocation, energy compaction BibRef

Yeo, Y., Shin, Y., Sagong, M., Kim, S., Ko, S.,
Simple Yet Effective Way for Improving the Performance of Lossy Image Compression,
SPLetters(27), 2020, pp. 530-534.
IEEE DOI 2005
Convolutional neural network, deep learning, image compression BibRef

Cai, J., Cao, Z., Zhang, L.,
Learning a Single Tucker Decomposition Network for Lossy Image Compression With Multiple Bits-per-Pixel Rates,
IP(29), 2020, pp. 3612-3625.
IEEE DOI 2002
Lossy image compression, convolutional neural networks, tucker decomposition BibRef

Schiopu, I., Munteanu, A.,
Deep-Learning-Based Lossless Image Coding,
CirSysVideo(30), No. 7, July 2020, pp. 1829-1842.
IEEE DOI 2007
Image coding, Cameras, Context modeling, Tools, Codecs, Prediction methods, Standards, Machine learning, image coding, context modeling BibRef

Liao, L.[Liang], Xiao, J.[Jing], Li, Y.T.[Ya-Ting], Wang, M.[Mi], Hu, R.M.[Rui-Min],
Learned Representation of Satellite Image Series for Data Compression,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
Long term background redundancy. BibRef

Klopp, J.P.[Jan P.], Chen, L.G.[Liang-Gee], Chien, S.Y.[Shao-Yi],
Utilising Low Complexity CNNs to Lift Non-Local Redundancies in Video Coding,
IP(29), 2020, pp. 6372-6385.
IEEE DOI 2006
Image coding, Redundancy, Decoding, Neural networks, Complexity theory, Video codecs, Noise reduction, Video coding, machine learning BibRef

Paul, S., Norkin, A., Bovik, A.C.,
Speeding Up VP9 Intra Encoder With Hierarchical Deep Learning-Based Partition Prediction,
IP(29), 2020, pp. 8134-8148.
IEEE DOI 2008
Machine learning, Image coding, Databases, Encoding, Video coding, Task analysis, Video codecs, VP9, video encoding, block partitioning, machine learning BibRef

Chen, L.H., Bampis, C.G., Li, Z., Norkin, A., Bovik, A.C.,
ProxIQA: A Proxy Approach to Perceptual Optimization of Learned Image Compression,
IP(30), 2021, pp. 360-373.
IEEE DOI 2012
Image coding, Optimization, Image quality, Training, Task analysis, Indexes, Loss measurement, Perceptual optimization, deep compression BibRef

Huang, C.[Chao], Peng, Z.J.[Zong-Ju], Xu, Y.[Yong], Chen, F.[Fen], Jiang, Q.P.[Qiu-Ping], Zhang, Y.[Yun], Jiang, G.Y.[Gang-Yi], Ho, Y.S.[Yo-Sung],
Online Learning-Based Multi-Stage Complexity Control for Live Video Coding,
IP(30), 2021, pp. 641-656.
IEEE DOI 2012
Complexity allocation, complexity control, high efficiency video coding, online learning, random forest BibRef

Chen, T., Liu, H., Ma, Z., Shen, Q., Cao, X., Wang, Y.,
End-to-End Learnt Image Compression via Non-Local Attention Optimization and Improved Context Modeling,
IP(30), 2021, pp. 3179-3191.
IEEE DOI 2103
Image coding, Context modeling, Transforms, Transform coding, Correlation, Complexity theory, variable-rate model BibRef

Kudo, S.[Shinobu], Orihashi, S.[Shota], Tanida, R.[Ryuichi], Takamura, S.[Seishi], Kimata, H.[Hideaki],
GAN-Based Image Compression Using Mutual Information for Optimizing Subjective Image Similarity,
IEICE(E104-D), No. 3, March 2021, pp. 450-460.
WWW Link. 2103
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Wang, J., Duan, Y., Tao, X., Xu, M., Lu, J.,
Semantic Perceptual Image Compression With a Laplacian Pyramid of Convolutional Networks,
IP(30), 2021, pp. 4225-4237.
IEEE DOI 2104
BibRef
Earlier: A1, A3, A4, A5, Only: ICIP19(699-703)
IEEE DOI 1910
Image coding, Laplace equations, Semantics, Generative adversarial networks, Training, Image reconstruction, perceptual quality. image compression, deep learning, Laplacian pyramid, adversarial network, perceptual loss BibRef

Ding, D.D.[Dan-Dan], Kong, L.[Lingyi], Wang, W.Y.[Wen-Yu], Zhu, F.Q.[Feng-Qing],
A progressive CNN in-loop filtering approach for inter frame coding,
SP:IC(94), 2021, pp. 116201.
Elsevier DOI 2104
CNN, In-loop filtering, Model training, Inter coding BibRef

Dua, Y.[Yaman], Singh, R.S.[Ravi Shankar], Parwani, K.[Kshitij], Lunagariya, S.[Smit], Kumar, V.[Vinod],
Convolution Neural Network based lossy compression of hyperspectral images,
SP:IC(95), 2021, pp. 116255.
Elsevier DOI 2106
Autoencoder, Lossy compression, Convolution Neural Network, Hyperspectral images, Learning based compression BibRef

Zhao, S.H.[Shi-Hui], Yang, S.Y.[Shu-Yuan], Gu, J.[Jing], Liu, Z.[Zhi], Feng, Z.X.[Zhi-Xi],
Symmetrical lattice generative adversarial network for remote sensing images compression,
PandRS(176), 2021, pp. 169-181.
Elsevier DOI 2106
Generative adversarial network, Remote sensing image compression, Symmetrical lattice, Cooperative learning BibRef

Chen, Y.H.[Yi-Hao], Tan, B.[Bin], Wu, J.[Jun], Zhang, Z.F.[Zhi-Feng], Ren, H.Q.[Hao-Qi],
A Deep Image Coding Scheme With Generative Network to Learn From Correlated Images,
MultMed(23), 2021, pp. 2235-2244.
IEEE DOI 2108
Image coding, Image reconstruction, Inverse problems, Generative adversarial networks, Generators, Deep learning, inverse problem BibRef

Liu, H.J.[Hao-Jie], Lu, M.[Ming], Ma, Z.[Zhan], Wang, F.[Fan], Xie, Z.H.[Zhi-Huang], Cao, X.[Xun], Wang, Y.[Yao],
Neural Video Coding Using Multiscale Motion Compensation and Spatiotemporal Context Model,
CirSysVideo(31), No. 8, August 2021, pp. 3182-3196.
IEEE DOI 2108
Video coding, Motion compensation, Encoding, Bit rate, Decoding, Image coding, Spatiotemporal phenomena, Neural video coding, temporal error propagation BibRef

Ding, D.D.[Dan-Dan], Ma, Z.[Zhan], Chen, D.[Di], Chen, Q.S.[Qing-Shuang], Liu, Z.[Zoe], Zhu, F.Q.[Feng-Qing],
Advances in Video Compression System Using Deep Neural Network: A Review and Case Studies,
PIEEE(109), No. 9, September 2021, pp. 1494-1520.
IEEE DOI 2108
Encoding, Video compression, Video coding, Streaming media, Visualization, Quality of experience, Spatiotemporal phenomena, texture analysis BibRef

Chen, T.[Tong], Liu, H.J.[Hao-Jie], Shen, Q.[Qiu], Yue, T.[Tao], Cao, X.[Xun], Ma, Z.[Zhan],
DeepCoder: A deep neural network based video compression,
VCIP17(1-4)
IEEE DOI 1804
Huffman codes, convolution, data compression, feedforward neural nets, video coding, video compression BibRef

Wang, Z.X.[Zi-Xi], Ding, G.G.[Gui-Guang], Han, J.G.[Jun-Gong], Li, F.[Fan],
Deep image compression with multi-stage representation,
JVCIR(79), 2021, pp. 103226.
Elsevier DOI 2109
Deep image compression, Multi-stage representation, Data-dependent probability model, Convolutional neural network BibRef

Lu, G.[Guo], Zhang, X.Y.[Xiao-Yun], Ouyang, W.L.[Wan-Li], Chen, L.[Li], Gao, Z.Y.[Zhi-Yong], Xu, D.[Dong],
An End-to-End Learning Framework for Video Compression,
PAMI(43), No. 10, October 2021, pp. 3292-3308.
IEEE DOI 2109
Image coding, Video compression, Optical imaging, Motion estimation, Optical distortion, Estimation, Adaptive optics, image compression BibRef

Lu, G.[Guo], Ouyang, W.L.[Wan-Li], Xu, D.[Dong], Zhang, X.Y.[Xiao-Yun], Cai, C.L.[Chun-Lei], Gao, Z.Y.[Zhi-Yong],
DVC: An End-To-End Deep Video Compression Framework,
CVPR19(10998-11007).
IEEE DOI 2002
BibRef

Hong, W.X.[Wei-Xin], Chen, T.[Tong], Lu, M.[Ming], Pu, S.L.[Shi-Liang], Ma, Z.[Zhan],
Efficient Neural Image Decoding via Fixed-Point Inference,
CirSysVideo(31), No. 9, September 2021, pp. 3618-3630.
IEEE DOI 2109
Image coding, Decoding, Task analysis, Convolutional codes, Transform coding, Quantization (signal), Dynamic range, range-dependent normalization BibRef

Sun, S.[Simeng], He, T.Y.[Tian-Yu], Chen, Z.B.[Zhi-Bo],
Semantic Structured Image Coding Framework for Multiple Intelligent Applications,
CirSysVideo(31), No. 9, September 2021, pp. 3631-3642.
IEEE DOI 2109
Image coding, Task analysis, Bit rate, Image reconstruction, Amplitude modulation, Semantics, Computational modeling, neural networks BibRef

Akbari, M.[Mohammad], Liang, J.[Jie], Han, J.[Jingning], Tu, C.J.[Cheng-Jie],
Learned Multi-Resolution Variable-Rate Image Compression With Octave-Based Residual Blocks,
MultMed(23), 2021, pp. 3013-3021.
IEEE DOI 2109
Image coding, Decoding, Convolutional codes, Transforms, Codecs, Image reconstruction, Linear programming, Deep learning, variable-rate BibRef

Zhang, F.[Fan], Ma, D.[Di], Feng, C.[Chen], Bull, D.R.[David R.],
Video Compression With CNN-Based Postprocessing,
MultMedMag(28), No. 4, October 2021, pp. 74-83.
IEEE DOI 2112
Encoding, Training, Generators, Image coding, Convolutional codes, Video compression, Tools BibRef

Karaca, A.C.[Ali Can], Kara, O.[Ozan], Güllü, M.K.[Mehmet Kemal],
MultiTempGAN: Multitemporal multispectral image compression framework using generative adversarial networks,
JVCIR(81), 2021, pp. 103385.
Elsevier DOI 2112
Multispectral image compression, Generative adversarial networks, Big data, Remote sensing, Multitemporal images BibRef

Ding, D.D.[Dan-Dan], Gao, X.[Xiang], Tang, C.[Chenran], Ma, Z.[Zhan],
Neural Reference Synthesis for Inter Frame Coding,
IP(31), 2022, pp. 773-787.
IEEE DOI 2201
Image coding, Image reconstruction, Training, Encoding, Quantization (signal), Correlation, neural reference synthesis BibRef

Chen, M.X.[Mei-Xu], Goodall, T.[Todd], Patney, A.[Anjul], Bovik, A.C.[Alan C.],
Learning to compress videos without computing motion,
SP:IC(103), 2022, pp. 116633.
Elsevier DOI 2203
Video compression, Deep learning, Motion BibRef

Guo, Z.Y.[Zong-Yu], Zhang, Z.Z.[Zhi-Zheng], Feng, R.S.[Run-Sen], Chen, Z.B.[Zhi-Bo],
Causal Contextual Prediction for Learned Image Compression,
CirSysVideo(32), No. 4, April 2022, pp. 2329-2341.
IEEE DOI 2204
Context modeling, Predictive models, Image coding, Entropy, Correlation, Entropy coding, Transforms, Learned image compression, improved entropy model BibRef

Ma, D.[Di], Zhang, F.[Fan], Bull, D.R.[David R.],
BVI-DVC: A Training Database for Deep Video Compression,
MultMed(24), 2022, pp. 3847-3858.
IEEE DOI 2208
Databases, Training, Spatial resolution, Encoding, Spatial databases, Standards, Video compression, Video database, BVI-DVC, CNN training, video compression BibRef

Mei, Y.X.[Yi-Xin], Li, L.[Li], Li, Z.[Zhu], Li, F.[Fan],
Learning-Based Scalable Image Compression With Latent-Feature Reuse and Prediction,
MultMed(24), 2022, pp. 4143-4157.
IEEE DOI 2208
Image coding, Standards, Redundancy, Streaming media, Scalability, Image reconstruction, Spatial resolution, convolutional neural network BibRef

Li, D.W.[Dao-Wen], Li, Y.M.[Ying-Ming], Sun, H.M.[He-Ming], Yu, L.[Lu],
Deep image compression based on multi-scale deformable convolution,
JVCIR(87), 2022, pp. 103573.
Elsevier DOI 2208
Deep image compression, Multi-scale deformable convolution, Spatial attention BibRef

Lopes, L.S.[Lucas S.], Chou, P.A.[Philip A.], de Queiroz, R.L.[Ricardo L.],
Adaptive Context Modeling for Arithmetic Coding Using Perceptrons,
SPLetters(29), 2022, pp. 2382-2386.
IEEE DOI 2212
Context modeling, Training, Adaptation models, Table lookup, Symbols, Encoding, Codes, Adaptive arithmetic coding, neural context modeling BibRef

Tang, Z.[Zhisen], Wang, H.[Hanli], Yi, X.K.[Xiao-Kai], Zhang, Y.[Yun], Kwong, S.[Sam], Kuo, C.C.J.[C.C. Jay],
Joint Graph Attention and Asymmetric Convolutional Neural Network for Deep Image Compression,
CirSysVideo(33), No. 1, January 2023, pp. 421-433.
IEEE DOI 2301
Image coding, Convolution, Convolutional neural networks, Training, Kernel, Visualization, Rate-distortion, Image compression, variational autoencoder BibRef

Ji, R.[Ruolei], Karam, L.J.[Lina J.],
Learning-based Visual Compression,
FTCGV(15), No. 1, 2023, pp. 1-112.
DOI Link 2302
Survey, Compression. BibRef

Guo, J.Y.[Jin-Yang], Xu, D.[Dong], Lu, G.[Guo],
CBANet: Toward Complexity and Bitrate Adaptive Deep Image Compression Using a Single Network,
IP(32), 2023, pp. 2049-2062.
IEEE DOI 2304
Image coding, Bit rate, Decoding, Computational complexity, Computational modeling, Adaptive systems, Rate-distortion, dynamic computational complexity BibRef

Fu, H.S.[Hai-Sheng], Liang, F.[Feng], Lin, J.P.[Jian-Ping], Li, B.[Bing], Akbari, M.[Mohammad], Liang, J.[Jie], Zhang, G.[Guohe], Liu, D.[Dong], Tu, C.J.[Cheng-Jie], Han, J.N.[Jing-Ning],
Learned Image Compression With Gaussian-Laplacian-Logistic Mixture Model and Concatenated Residual Modules,
IP(32), 2023, pp. 2063-2076.
IEEE DOI 2304
Image coding, Entropy, Entropy coding, Decoding, Correlation, Context modeling, Complexity theory, residual network BibRef

Bao, Y.[Youneng], Meng, F.Y.[Fan-Yang], Li, C.[Chao], Ma, S.W.[Si-Wei], Tian, Y.H.[Yong-Hong], Liang, Y.S.[Yong-Sheng],
Nonlinear Transforms in Learned Image Compression From a Communication Perspective,
CirSysVideo(33), No. 4, April 2023, pp. 1922-1936.
IEEE DOI 2304
Transforms, Modulation, Image coding, Communication systems, Quantization (signal), Mathematical models, Context modeling, nonlinear transform BibRef

Yang, Y.[Yibo], Mandt, S.[Stephan], Theis, L.[Lucas],
An Introduction to Neural Data Compression,
FTCGV(15), No. 2, 2023, pp. 113-200.
DOI Link 2305
Survey, Compression. BibRef

Jin, D.C.[Deng-Chao], Lei, J.J.[Jian-Jun], Peng, B.[Bo], Pan, Z.Q.[Zhao-Qing], Li, L.[Li], Ling, N.[Nam],
Learned Video Compression With Efficient Temporal Context Learning,
IP(32), 2023, pp. 3188-3198.
IEEE DOI 2306
Image coding, Video compression, Transforms, Codecs, Quantization (signal), Video coding, Motion compensation, TCVC-Net BibRef

Sheng, X.H.[Xi-Hua], Li, J.H.[Jia-Hao], Li, B.[Bin], Li, L.[Li], Liu, D.[Dong], Lu, Y.[Yan],
Temporal Context Mining for Learned Video Compression,
MultMed(25), 2023, pp. 7311-7322.
IEEE DOI 2311
BibRef

Wang, S.R.[Shu-Run], Wang, Z.[Zhao], Wang, S.Q.[Shi-Qi], Ye, Y.[Yan],
Deep Image Compression Toward Machine Vision: A Unified Optimization Framework,
CirSysVideo(33), No. 6, June 2023, pp. 2979-2989.
IEEE DOI 2306
Visualization, Image coding, Machine vision, Transform coding, Task analysis, Feature extraction, Bit rate, Image compression, machine vision BibRef

Lee, S.[Soonbin], Jeong, J.B.[Jong-Beom], Ryu, E.S.[Eun-Seok],
Entropy-Constrained Implicit Neural Representations for Deep Image Compression,
SPLetters(30), 2023, pp. 663-667.
IEEE DOI 2307
Image coding, Entropy, Computational modeling, Training, Data models, Neural networks, Distortion, Image compression, model compression, implicit neural representation BibRef

Lin, K.[Kai], Jia, C.M.[Chuan-Min], Zhang, X.F.[Xin-Feng], Wang, S.S.[Shan-She], Ma, S.W.[Si-Wei], Gao, W.[Wen],
DMVC: Decomposed Motion Modeling for Learned Video Compression,
CirSysVideo(33), No. 7, July 2023, pp. 3502-3515.
IEEE DOI 2307
Image coding, Spatiotemporal phenomena, Image reconstruction, Encoding, Video coding, Redundancy, Entropy, Video coding, motion compensation BibRef

Guo, Z.Y.[Zong-Yu], Feng, R.[Runsen], Zhang, Z.Z.[Zhi-Zheng], Jin, X.[Xin], Chen, Z.B.[Zhi-Bo],
Learning Cross-Scale Weighted Prediction for Efficient Neural Video Compression,
IP(32), 2023, pp. 3567-3579.
IEEE DOI 2307
Image coding, Video codecs, Predictive models, Video compression, Standards, Quantization (signal), Decoding, Video compression, quantization BibRef

Yang, R.[Ruihan], Yang, Y.[Yibo], Marino, J.[Joseph], Mandt, S.[Stephan],
Insights From Generative Modeling for Neural Video Compression,
PAMI(45), No. 8, August 2023, pp. 9908-9921.
IEEE DOI 2307
Transforms, Video compression, Data models, Image coding, Predictive coding, Streaming media, Rate-distortion, video compression BibRef

Gao, X.Y.[Xin-Yu], Mou, J.[Jun], Banerjee, S.[Santo], Zhang, Y.S.[Yu-Shu],
Color-Gray Multi-Image Hybrid Compression-Encryption Scheme Based on BP Neural Network and Knight Tour,
Cyber(53), No. 8, August 2023, pp. 5037-5047.
IEEE DOI 2307
Image coding, Encryption, Gray-scale, Image color analysis, Heuristic algorithms, Color, Neural network compression, multi-image (MI) BibRef

Fu, H.S.[Hai-Sheng], Liang, F.[Feng], Liang, J.[Jie], Li, B.L.[Bing-Lin], Zhang, G.[Guohe], Han, J.N.[Jing-Ning],
Asymmetric Learned Image Compression With Multi-Scale Residual Block, Importance Scaling, and Post-Quantization Filtering,
CirSysVideo(33), No. 8, August 2023, pp. 4309-4321.
IEEE DOI 2308
Image coding, Decoding, Complexity theory, Quantization (signal), Entropy coding, Bit rate, Measurement BibRef

Luo, S.[Sihui], Fang, G.F.[Gong-Fan], Song, M.L.[Ming-Li],
Deep semantic image compression via cooperative network pruning,
JVCIR(95), 2023, pp. 103897.
Elsevier DOI 2309
Deep image compression, Network pruning, Semantic perception BibRef

Duan, W.H.[Wen-Hong], Chang, Z.[Zheng], Jia, C.M.[Chuan-Min], Wang, S.S.[Shan-She], Ma, S.W.[Si-Wei], Song, L.[Li], Gao, W.[Wen],
Learned Image Compression Using Cross-Component Attention Mechanism,
IP(32), 2023, pp. 5478-5493.
IEEE DOI 2310
BibRef

Nami, S.[Sanaz], Pakdaman, F.[Farhad], Hashemi, M.R.[Mahmoud Reza], Shirmohammadi, S.[Shervin],
BL-JUNIPER: A CNN-Assisted Framework for Perceptual Video Coding Leveraging Block-Level JND,
MultMed(25), 2023, pp. 5077-5092.
IEEE DOI 2311
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Li, J.H.[Jia-Hao], Li, B.[Bin], Lu, Y.[Yan],
Neural Video Compression with Diverse Contexts,
CVPR23(22616-22626)
IEEE DOI 2309
BibRef

Hu, Z.H.[Zhi-Hao], Xu, D.[Dong],
Complexity-guided Slimmable Decoder for Efficient Deep Video Compression,
CVPR23(14358-14367)
IEEE DOI 2309
BibRef

Hojjat, A.[Ali], Haberer, J.[Janek], Landsiedel, O.[Olaf],
ProgDTD: Progressive Learned Image Compression with Double-Tail-Drop Training,
NTIRE23(1130-1139)
IEEE DOI 2309
BibRef

Qi, L.F.[Lin-Feng], Li, J.H.[Jia-Hao], Li, B.[Bin], Li, H.Q.[Hou-Qiang], Lu, Y.[Yan],
Motion Information Propagation for Neural Video Compression,
CVPR23(6111-6120)
IEEE DOI 2309
BibRef

Mital, N.[Nitish], Özyilkan, E.[Ezgi], Garjani, A.[Ali], Gündüz, D.[Deniz],
Neural Distributed Image Compression with Cross-Attention Feature Alignment,
WACV23(2497-2506)
IEEE DOI 2302
Correlated image avaliable on decoder side. Image coding, Source coding, Pipelines, Neural networks, Transforms, Cameras, Entropy coding BibRef

Tsubota, K.[Koki], Akutsu, H.[Hiroaki], Aizawa, K.[Kiyoharu],
Universal Deep Image Compression via Content-Adaptive Optimization with Adapters,
WACV23(2528-2537)
IEEE DOI 2302
Adaptation models, Image coding, Codes, Transform coding, Rate-distortion, Benchmark testing, image and video synthesis BibRef

Brummer, B.[Benoit], de Vleeschouwer, C.[Christophe],
On the Importance of Denoising when Learning to Compress Images,
WACV23(2439-2447)
IEEE DOI 2302
Training, Adaptation models, Image coding, Noise reduction, Rate-distortion, Transform coding, Noise measurement BibRef

Li, M.[Meng], Gao, S.Y.[Shang-Yin], Feng, Y.H.[Yi-Hui], Shi, Y.[Yibo], Wang, J.[Jing],
Content-Oriented Learned Image Compression,
ECCV22(XIX:632-647).
Springer DOI 2211
BibRef

Shi, Y.[Yibo], Ge, Y.Y.[Yun-Ying], Wang, J.[Jing], Mao, J.[Jue],
AlphaVC: High-Performance and Efficient Learned Video Compression,
ECCV22(XIX:616-631).
Springer DOI 2211
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Wang, F.[Feng], Chen, J.Y.[Jing-Yi], Wang, R.G.[Rong-Gang],
Entropy-Reduced Attention for Image Compression,
ICIP22(2401-2405)
IEEE DOI 2211
Deep learning, Image coding, Uncertainty, Redundancy, Entropy, Entropy coding, Decoding, Deep Learning, Image Compression, Attention Mechanism BibRef

Brand, F.[Fabian], Seiler, J.[Jürgen], Kaup, A.[André],
P-Frame Coding with Generalized Difference: A Novel Conditional Coding Approach,
ICIP22(1266-1270)
IEEE DOI 2211
Image coding, Redundancy, Transform coding, Focusing, Switches, Video compression, Complexity theory, Video Compression, Deep Learning BibRef

Koyuncu, A.B.[A. Burakhan], Gao, H.[Han], Boev, A.[Atanas], Gaikov, G.[Georgii], Alshina, E.[Elena], Steinbach, E.[Eckehard],
Contextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compression,
ECCV22(XIX:447-463).
Springer DOI 2211
BibRef

Cheng, K.L.[Ka Leong], Xie, Y.[Yueqi], Chen, Q.F.[Qi-Feng],
Optimizing Image Compression via Joint Learning with Denoising,
ECCV22(XIX:56-73).
Springer DOI 2211
BibRef

Liu, C.[Chao], Sun, H.M.[He-Ming], Zeng, X.Y.[Xiao-Yang], Fan, Y.[Yibo],
Learned Video Compression With Residual Prediction And Feature-Aided Loop Filter,
ICIP22(1321-1325)
IEEE DOI 2211
Image coding, Redundancy, Video compression, Predictive models, Motion compensation, Complexity theory, Decoding, residual prediction BibRef

Liu, Z.Y.[Zi-Yi], Wang, H.[Hanli], Su, T.[Taiyi],
Learned Image Compression with Multi-Scale Spatial and Contextual Information Fusion,
ICIP22(706-710)
IEEE DOI 2211
Video coding, Visualization, Solid modeling, Image coding, Convolution, Neural networks, Image compression, deep learning, multi-scale 3D context BibRef

Zhang, Z.B.[Zhao-Bin], Li, Y.[Yue], Zhang, K.[Kai], Zhang, L.[Li], He, Y.[Yuwen],
Learning-Based End-to-End Video Compression with Spatial-Temporal Adaptation,
ICIP22(2821-2825)
IEEE DOI 2211
Interpolation, Image coding, Correlation, Redundancy, Rate-distortion, Switches, Video compression, frame extrapolation BibRef

Zhang, G.[Gai], Zhang, X.F.[Xin-Feng], Zhu, S.Y.[Shu-Yuan],
Local and Global Fusion Network for Learned Image Compression,
ICIP22(3763-3767)
IEEE DOI 2211
Video coding, Image coding, Convolution, Fuses, Neural networks, Redundancy, Information retrieval, Image compression, autoencoder BibRef

Pan, G.B.[Guan-Bo], Lu, G.[Guo], Hu, Z.H.[Zhi-Hao], Xu, D.[Dong],
Content Adaptive Latents and Decoder for Neural Image Compression,
ECCV22(XVIII:556-573).
Springer DOI 2211
Neural compression, usually not adaptive. BibRef

Said, A.[Amir], Pourreza, R.[Reza], Le, H.[Hoang],
Optimized Learned Entropy Coding Parameters for Practical Neural-Based Image and Video Compression,
ICIP22(661-665)
IEEE DOI 2211
Quantization (signal), Image coding, Codes, Redundancy, Memory management, Video compression, Minimization, entropy coding BibRef

Lin, F.Z.[Fang-Zheng], Sun, H.M.[He-Ming], Katto, J.[Jiro],
Streaming-Capable High-Performance Architecture of Learned Image Compression Codecs,
ICIP22(286-290)
IEEE DOI 2211
Performance evaluation, Image coding, Runtime, Codecs, Computational modeling, Streaming media, pipelining BibRef

Wang, H.R.[Huai-Rui], Ren, G.J.[Guang-Jie], Ouyang, T.[Tong], Zhang, J.X.[Jun-Xi], Han, W.W.[Wen-Wei], Liu, Z.Z.[Zi-Zheng], Chen, Z.Z.[Zhen-Zhong],
Perceptual in-Loop Filter for Image and Video Compression,
CLIC22(1769-1772)
IEEE DOI 2210
Visualization, Image coding, Focusing, Video compression, Generative adversarial networks BibRef

Lu, G.[Guo], Zhong, T.X.[Tian-Xiong], Geng, J.[Jing], Hu, Q.A.[Qi-Ang], Xu, D.[Dong],
Learning based Multi-modality Image and Video Compression,
CVPR22(6073-6082)
IEEE DOI 2210
Visualization, Image coding, Correlation, Redundancy, Transforms, Video compression, Low-level vision, 3D from multi-view and sensors BibRef

He, D.[Dailan], Yang, Z.M.[Zi-Ming], Peng, W.[Weikun], Ma, R.[Rui], Qin, H.W.[Hong-Wei], Wang, Y.[Yan],
ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding,
CVPR22(5708-5717)
IEEE DOI 2210
Adaptation models, Image coding, Computational modeling, Transforms, Decoding, Low-level vision BibRef

He, D.[Dailan], Yang, Z.M.[Zi-Ming], Yu, H.J.[Hong-Jiu], Xu, T.[Tongda], Luo, J.X.[Ji-Xiang], Chen, Y.[Yuan], Gao, C.J.[Chen-Jian], Shi, X.[Xinjie], Qin, H.W.[Hong-Wei], Wang, Y.[Yan],
PO-ELIC: Perception-Oriented Efficient Learned Image Coding,
CLIC22(1763-1768)
IEEE DOI 2210
Measurement, Training, Image quality, Adaptation models, Visualization, Image coding, Image color analysis BibRef

Sigger, N.[Neetu], Al-Jawed, N.[Naseer], Nguyen, T.[Tuan],
Spatial-Temporal Autoencoder with Attention Network for Video Compression,
CIAP22(III:290-300).
Springer DOI 2205
BibRef

Gao, G.[Ge], You, P.[Pei], Pan, R.[Rong], Han, S.Y.[Shun-Yuan], Zhang, Y.Y.[Yuan-Yuan], Dai, Y.C.[Yu-Chao], Lee, H.[Hojae],
Neural Image Compression via Attentional Multi-scale Back Projection and Frequency Decomposition,
ICCV21(14657-14666)
IEEE DOI 2203
Training, Video coding, Image coding, Estimation, Standards, Next generation networking, Image and video synthesis, Vision applications and systems BibRef

Liu, J.M.[Jia-Ming], Lu, M.[Ming], Chen, K.X.[Kai-Xin], Li, X.Q.[Xiao-Qi], Wang, S.Z.[Shi-Zun], Wang, Z.Q.[Zhao-Qing], Wu, E.[Enhua], Chen, Y.R.[Yu-Rong], Zhang, C.[Chuang], Wu, M.[Ming],
Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation,
ICCV21(4611-4620)
IEEE DOI 2203
Training, Video coding, Neural networks, Modulation, Streaming media, Explosions, Internet, Low-level and physics-based vision, Vision applications and systems BibRef

Fischer, K.[Kristian], Forsch, C.[Christian], Herglotz, C.[Christian], Kaup, A.[André],
Analysis of Neural Image Compression Networks for Machine-To-Machine Communication,
ICIP21(2079-2083)
IEEE DOI 2201
Training, Weight measurement, Video coding, Machine-to-machine communications, Image coding, Codecs BibRef

Haase, P.[Paul], Becking, D.[Daniel], Kirchhoffer, H.[Heiner], Müller, K.[Karsten], Schwarz, H.[Heiko], Samek, W.[Wojciech], Marpe, D.[Detlev], Wiegand, T.[Thomas],
Encoder Optimizations for the NNR Standard on Neural Network Compression,
ICIP21(3522-3526)
IEEE DOI 2201
Image coding, Quantization (signal), Tensors, Transform coding, Optimization methods, Artificial neural networks, Tools, MPEG, NNR, encoder optimization BibRef

Yílmaz, M.A.[M. Akín], Keless, O.[Onur], Güven, H.[Hilal], Tekalp, A.M.[A. Murat], Malik, J.[Junaid], Kíranyaz, S.[Serkan],
Self-Organized Variational Autoencoders (Self-Vae) for Learned Image Compression,
ICIP21(3732-3736)
IEEE DOI 2201
Convolutional codes, Measurement, Visualization, Image coding, Codecs, Neurons, Rate-distortion, perceptual quality metrics BibRef

Mikami, Y.[Yu], Tsutake, C.[Chihiro], Takahashi, K.[Keita], Fujii, T.[Toshiaki],
An Efficient Image Compression Method Based on Neural Network: An Overfitting Approach,
ICIP21(2084-2088)
IEEE DOI 2201
Image quality, Visualization, Image coding, Quantization (signal), Image edge detection, Rate-distortion, parameter visualization BibRef

Tsubota, K.[Koki], Aizawa, K.[Kiyoharu],
Comprehensive Comparisons of Uniform Quantizers for Deep Image Compression,
ICIP21(2089-2093)
IEEE DOI 2201
Quantization (signal), Image coding, Rate-distortion, Focusing, Entropy, Entropy coding, Image Compression, Neural Networks, Quantization BibRef

Yang, C.H.[Chun-Hui], Ma, Y.[Yi], Yang, J.Y.[Jia-Yu], Liu, S.Y.[Shi-Yi], Wang, R.G.[Rong-Gang],
Graph-Convolution Network for Image Compression,
ICIP21(2094-2098)
IEEE DOI 2201
Image coding, Quantization (signal), Convolution, Neural networks, Feature extraction, Entropy, Image compression, graph convolution, deep learning BibRef

Yuan, L.[Liang], Luo, J.X.[Ji-Xiang], Li, S.H.[Shao-Hui], Dai, W.[Wenrui], Li, C.[Chenglin], Zou, J.[Junni], Xiong, H.K.[Hong-Kai],
Learned Image Compression with Channel-Wise Grouped Context Modeling,
ICIP21(2099-2103)
IEEE DOI 2201
Deep learning, Solid modeling, Image coding, Correlation, Redundancy, Rate-distortion, Entropy coding, Image compression, coding efficiency BibRef

Dick, J.[João], Abreu, B.[Brunno], Grellert, M.[Mateus], Bampi, S.[Sergio],
Quality and Complexity Assessment of Learning-Based Image Compression Solutions,
ICIP21(599-603)
IEEE DOI 2201
Measurement, Visualization, Image coding, Codecs, Bit rate, Transform coding, image compression, learning-based BibRef

He, D.[Dailan], Zheng, Y.Y.[Yao-Yan], Sun, B.C.[Bao-Cheng], Wang, Y.[Yan], Qin, H.W.[Hong-Wei],
Checkerboard Context Model for Efficient Learned Image Compression,
CVPR21(14766-14775)
IEEE DOI 2111
Image coding, Computational modeling, Redundancy, Rate-distortion, Decoding, Pattern recognition BibRef

Liu, Y.C.[Yu-Chen], Shu, Z.X.[Zhi-Xin], Li, Y.J.[Yi-Jun], Lin, Z.[Zhe], Perazzi, F.[Federico], Kung, S.Y.,
Content-Aware GAN Compression,
CVPR21(12151-12161)
IEEE DOI 2111
Manifolds, Image quality, Visualization, Image coding, Image synthesis, Pipelines, Generative adversarial networks BibRef

Weber, M.[Maurice], Renggli, C.[Cedric], Grabner, H.[Helmut], Zhang, C.[Ce],
Observer Dependent Lossy Image Compression,
GCPR20(130-144).
Springer DOI 2110
BibRef

Ho, Y.H.[Yung-Han], Chang, C.P.[Chih-Peng], Chen, P.Y.[Peng-Yu], Gnutti, A.[Alessandro], Peng, W.H.[Wen-Hsiao],
CANF-VC: Conditional Augmented Normalizing Flows for Video Compression,
ECCV22(XVI:207-223).
Springer DOI 2211
BibRef

Ho, Y.H.[Yung-Han], Chan, C.C.[Chih-Chun], Peng, W.H.[Wen-Hsiao], Hang, H.M.[Hsueh-Ming],
End-to-End Learned Image Compression with Augmented Normalizing Flows,
CLIC21(1931-1935)
IEEE DOI 2109
Image coding, Stacking, Low-pass filters, Transforms, Predictive models BibRef

Suzuki, A.[Akifumi], Akutsu, H.[Hiroaki], Naruko, T.[Takahiro], Tsubota, K.[Koki], Aizawa, K.[Kiyoharu],
Learned Image Compression with Super-Resolution Residual Modules and DISTS Optimization,
CLIC21(1906-1910)
IEEE DOI 2109
Image quality, Measurement, Visualization, Image coding, Superresolution, Bit rate, Decoding BibRef

Gao, Y.X.[Yi-Xin], Wu, Y.[Yaojun], Guo, Z.[Zongyu], Zhang, Z.Z.[Zhi-Zheng], Chen, Z.B.[Zhi-Bo],
Perceptual Friendly Variable Rate Image Compression,
CLIC21(1916-1920)
IEEE DOI 2109
Measurement, Training, Visualization, Adaptation models, Image coding, Rate-distortion BibRef

Islam, K.[Khawar], Dang, L.M.[L. Minh], Lee, S.[Sujin], Moon, H.[Hyeonjoon],
Image Compression with Recurrent Neural Network and Generalized Divisive Normalization,
CLIC21(1875-1879)
IEEE DOI 2109
Image coding, Recurrent neural networks, Quantization (signal), Convolution, Redundancy, Transform coding, Decoding BibRef

Zhao, J.[Jing], Li, B.[Bin], Li, J.H.[Jia-Hao], Xiong, R.Q.[Rui-Qin], Lu, Y.[Yan],
A Universal Encoder Rate Distortion Optimization Framework for Learned Compression,
CLIC21(1880-1884)
IEEE DOI 2109
Image coding, Codecs, Bit rate, Rate-distortion, Optimization methods BibRef

Xu, Y.[Yi], Zhao, M.[Minyi], Liu, J.[Jing], Zhang, X.J.[Xin-Jian], Gao, L.[Longwen], Zhou, S.[Shuigeng], Sun, H.Y.[Hu-Yang],
Boosting the Performance of Video Compression Artifact Reduction with Reference Frame Proposals and Frequency Domain Information,
NTIRE21(213-222)
IEEE DOI 2109
Deep learning, Frequency-domain analysis, Video compression, Boosting, Spatiotemporal phenomena BibRef

Peng, W.H., Hang, H.M.,
Recent Advances in End-to-End Learned Image and Video Compression,
VCIP20(1-2)
IEEE DOI 2102
Image coding, Transform coding, Standards, Video compression, Streaming media, MPEG standards, High efficiency video coding BibRef

Xu, D., Lu, G., Yang, R., Timofte, R.,
Learned image and video compression with deep neural networks,
VCIP20(1-3)
IEEE DOI 2102
Image coding, Data compression, Video compression, Deep learning, Tutorials BibRef

Ayzik, S.[Sharon], Avidan, S.[Shai],
Deep Image Compression Using Decoder Side Information,
ECCV20(XVII:699-714).
Springer DOI 2011
Code, Compression.
WWW Link. Information available only to the decoder. Learn the transformation. BibRef

Su, R., Cheng, Z., Sun, H., Katto, J.,
Scalable Learned Image Compression With A Recurrent Neural Networks-Based Hyperprior,
ICIP20(3369-3373)
IEEE DOI 2011
Image coding, Entropy, Quantization (signal), Transform coding, Entropy coding, Recurrent neural networks, Transforms, RNN-based hyperprior BibRef

Guarda, A.F.R., Rodrigues, N.M.M., Pereira, F.,
Point Cloud Geometry Scalable Coding With a Single End-to-End Deep Learning Model,
ICIP20(3354-3358)
IEEE DOI 2011
Encoding, Geometry, Decoding, Transform coding, Standards, Training, Point cloud coding, quality scalability BibRef

Singh, S., Abu-El-Haija, S., Johnston, N., Ballé, J., Shrivastava, A., Toderici, G.,
End-to-End Learning of Compressible Features,
ICIP20(3349-3353)
IEEE DOI 2011
Image coding, Task analysis, Training, Quantization (signal), Distortion, Entropy, Principal component analysis, Neural networks BibRef

Bhagat, S.[Sarthak], Uppal, S.[Shagun], Yin, Z.Y.[Zhu-Yun], Lim, N.L.[Neng-Li],
Disentangling Multiple Features in Video Sequences Using Gaussian Processes in Variational Autoencoders,
ECCV20(XXIII:102-117).
Springer DOI 2011
Multiple features, static or dynamic, can be disentangled. BibRef

Lu, G.[Guo], Cai, C.L.[Chun-Lei], Zhang, X.Y.[Xiao-Yun], Chen, L.[Li], Ouyang, W.L.[Wan-Li], Xu, D.[Dong], Gao, Z.Y.[Zhi-Yong],
Content Adaptive and Error Propagation Aware Deep Video Compression,
ECCV20(II:456-472).
Springer DOI 2011
BibRef

Hu, Z.H.[Zhi-Hao], Chen, Z.H.[Zheng-Hao], Xu, D.[Dong], Lu, G.[Guo], Ouyang, W.L.[Wan-Li], Gu, S.H.[Shu-Hang],
Improving Deep Video Compression by Resolution-adaptive Flow Coding,
ECCV20(II:193-209).
Springer DOI 2011
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Sun, W.Y.[Wen-Yu], Tang, C.[Chen], Li, W.[Weigui], Yuan, Z.Q.[Zhu-Qing], Yang, H.Z.[Hua-Zhong], Liu, Y.[Yongpan],
High-quality Single-model Deep Video Compression with Frame-Conv3D and Multi-frame Differential Modulation,
ECCV20(XXX: 239-254).
Springer DOI 2010
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Xu, J., Lytchier, A., Cursio, C., Kollias, D., Besenbruch, C., Zafar, A.,
Efficient Context-Aware Lossy Image Compression,
CLIC20(552-554)
IEEE DOI 2008
Context modeling, Image coding, Training, Pipelines, Decoding, Computational modeling BibRef

Sun, H., Liu, C., Katto, J., Fan, Y.,
An Image Compression Framework with Learning-based Filter,
CLIC20(602-606)
IEEE DOI 2008
Image color analysis, Principal component analysis, Image coding, Image reconstruction, Distortion, Correlation, Covariance matrices BibRef

Tao, H., Qian, J., Yu, L., Wang, H., Zhang, W., Li, Z., Wang, N., Zeng, X.,
Post-Processing Network Based on Dense Inception Attention for Video Compression,
CLIC20(547-551)
IEEE DOI 2008
Encoding, Video compression, Video coding, Image coding, Feature extraction, Kernel, Standards BibRef

Feng, R., Wu, Y., Guo, Z., Zhang, Z., Chen, Z.,
Learned Video Compression with Feature-level Residuals,
CLIC20(529-532)
IEEE DOI 2008
Image coding, Training, Optical imaging, Adaptive optics, Motion compensation, Optical distortion, Decoding BibRef

Akutsu, H., Suzuki, A., Zhong, Z., Aizawa, K.,
Ultra Low Bitrate Learned Image Compression by Selective Detail Decoding,
CLIC20(524-528)
IEEE DOI 2008
Decoding, Image coding, Entropy, Training, Bit rate, Random access memory, Indexes BibRef

He, G., Wu, C., Li, L., Zhou, J., Wang, X., Zheng, Y., Yu, B., Xie, W.,
A Video Compression Framework Using an Overfitted Restoration Neural Network,
CLIC20(593-597)
IEEE DOI 2008
Video compression, Image restoration, Neural networks, Training, Decoding, Pattern recognition BibRef

Zou, N.N.[Nan-Nan], Zhang, H.L.[Hong-Lei], Cricri, F.[Francesco], Tavakoli, H.R.[Hamed R.], Lainema, J.[Jani], Aksu, E.[Emre], Hannuksela, M.[Miska], Rahtu, E.[Esa],
Learned Video Compression with Intra-Guided Enhancement and Implicit Motion Information,
CLIC21(1870-1874)
IEEE DOI 2109
BibRef
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End-to-End Learning for Video Frame Compression with Self-Attention,
CLIC20(580-584)
IEEE DOI 2008
Image coding, Computational modeling, Pipelines, MIMICs, Video compression. Decoding, Neural networks, Tensile stress, Context modeling, Image coding, Adaptation models, Probability distribution BibRef

Lin, C., Yao, J., Chen, F., Wang, L.,
A Spatial RNN Codec for End-to-End Image Compression,
CVPR20(13266-13274)
IEEE DOI 2008
Image coding, Quantization (signal), Standards, Entropy, Computational modeling, Redundancy, Transforms BibRef

Chin, T., Ding, R., Zhang, C., Marculescu, D.,
Towards Efficient Model Compression via Learned Global Ranking,
CVPR20(1515-1525)
IEEE DOI 2008
Complexity theory, Art, Drones, Autonomous robots, Computational modeling BibRef

Quach, M., Valenzise, G., Dufaux, F.,
Learning Convolutional Transforms for Lossy Point Cloud Geometry Compression,
ICIP19(4320-4324)
IEEE DOI 1910
point cloud geometry compression, convolutional neural network, rate-distortion optimization BibRef

Agustsson, E.[Eirikur], Minnen, D.[David], Toderici, G.[George], Mentzer, F.[Fabian],
Multi-Realism Image Compression with a Conditional Generator,
CVPR23(22324-22333)
IEEE DOI 2309
BibRef

Mentzer, F.[Fabian], Agustsson, E.[Eirikur], Tschannen, M.[Michael], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Practical Full Resolution Learned Lossless Image Compression,
CVPR19(10621-10630).
IEEE DOI 2002
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Yang, J., Yang, C., Ma, Y., Liu, S., Wang, R.,
Learned Low Bit-rate Image Compression with Adversarial Mechanism,
CLIC20(575-579)
IEEE DOI 2008
Image coding, Image reconstruction, Decoding, Training, Entropy, Estimation, Distortion BibRef

Huang, C.C.[Ching-Chun], Nguyen, T.P.[Thanh-Phat], Lai, C.T.[Chen-Tung],
Multi-Channel Multi-Loss Deep Learning Based Compression Model of Color Images,
ICIP19(4524-4528)
IEEE DOI 1910
CNN, Deep image compression, Color shift reduction BibRef

Lin, J., Liu, D., Li, H., Wu, F.,
M-LVC: Multiple Frames Prediction for Learned Video Compression,
CVPR20(3543-3551)
IEEE DOI 2008
Video compression, Image coding, Motion compensation, Entropy, Encoding, Motion estimation, Transforms BibRef

Yang, R., Mentzer, F., Van Gool, L.J., Timofte, R.,
Learning for Video Compression With Hierarchical Quality and Recurrent Enhancement,
CVPR20(6627-6636)
IEEE DOI 2008
Image coding, Video compression, Decoding, Bidirectional control, Streaming media, Rate-distortion, Correlation BibRef

Mentzer, F., Van Gool, L.J., Tschannen, M.,
Learning Better Lossless Compression Using Lossy Compression,
CVPR20(6637-6646)
IEEE DOI 2008
Image coding, Image reconstruction, Probabilistic logic, Entropy coding, Bit rate, Decoding, Transform coding BibRef

Luo, A.[Ao], Sun, H.M.[He-Ming], Liu, J.M.[Jin-Ming], Katto, J.[Jiro],
Memory-Efficient Learned Image Compression with Pruned Hyperprior Module,
ICIP22(3061-3065)
IEEE DOI 2211
Performance evaluation, Image coding, Costs, Deconvolution, Image edge detection, Memory management, Rate-distortion, Model Pruning BibRef

Cheng, Z.X.[Zheng-Xue], Sun, H.M.[He-Ming], Takeuchi, M.[Masaru], Katto, J.[Jiro],
Learned Image Compression With Discretized Gaussian Mixture Likelihoods and Attention Modules,
CVPR20(7936-7945)
IEEE DOI 2008
BibRef
And: A1, A2, A4, Only:
Low Bitrate Image Compression with Discretized Gaussian Mixture Likelihoods,
CLIC20(543-546)
IEEE DOI 2008
Image coding, Entropy, Standards, Visualization, Training, Redundancy, Transform coding. Convolution, Training, Decoding, Pattern recognition, Bit rate BibRef

Djelouah, A., Campos, J., Schaub-Meyer, S., Schroers, C.[Christopher],
Neural Inter-Frame Compression for Video Coding,
ICCV19(6420-6428)
IEEE DOI 2004
data compression, decoding, image sequences, interpolation, learning (artificial intelligence), motion compensation, Distortion BibRef

Lucas, A., Lopez-Tapia, S., Molina, R., Katsaggelos, A.K.,
Efficient Fine-Tuning of Neural Networks for Artifact Removal in Deep Learning for Inverse Imaging Problems,
ICIP19(3591-3595)
IEEE DOI 1910
Deep Neural Networks, Image and Video Processing, Inversion, Fine-tuning, Artifacts, Data Consistency BibRef

Rippel, O., Nair, S., Lew, C., Branson, S., Anderson, A., Bourdev, L.,
Learned Video Compression,
ICCV19(3453-3462)
IEEE DOI 2004
data compression, image sequences, learning (artificial intelligence), motion estimation, Video codecs BibRef

Cheng, Z.X.[Zheng-Xue], Sun, H.M.[He-Ming], Takeuchi, M.[Masaru], Katto, J.[Jiro],
Learning Image and Video Compression Through Spatial-Temporal Energy Compaction,
CVPR19(10063-10072).
IEEE DOI 2002
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Westland, N., Dias, A.S., Mrak, M.,
Decision Trees for Complexity Reduction in Video Compression,
ICIP19(2666-2670)
IEEE DOI 1910
Video Coding, Complexity Reduction, Machine Learning, Decision Trees BibRef

Su, H., Tsai, C., Wang, Y., Xu, Y.,
Machine Learning Accelerated Partition Search for Video Encoding,
ICIP19(2661-2665)
IEEE DOI 1910
Video Coding, Machine Learning, Partition Search, Encoding Speedup, VP9 BibRef

Kumar, S.[Saurabh], Chaudhuri, S.[Subhasis], Banerjee, B.[Biplab], Ali, F.[Feroz],
Onboard Hyperspectral Image Compression Using Compressed Sensing and Deep Learning,
CVUAV18(II:30-42).
Springer DOI 1905
BibRef

Nakanishi, K.M.[Ken M.], Maeda, S.I.[Shin-Ichi], Miyato, T.[Takeru], Okanohara, D.[Daisuke],
Neural Multi-scale Image Compression,
ACCV18(VI:718-732).
Springer DOI 1906
consists of two networks: multi-scale lossy autoencoder and parallel multi-scale lossless coder. BibRef

He, X.Y.[Xiang-Yu], Cheng, J.[Jian],
Learning Compression from Limited Unlabeled Data,
ECCV18(I: 778-795).
Springer DOI 1810
BibRef

Xu, K.[Kai], Ren, F.[Fengbo],
CSVideoNet: A Real-Time End-to-End Learning Framework for High-Frame-Rate Video Compressive Sensing,
WACV18(1680-1688)
IEEE DOI 1806
cameras, compressed sensing, data compression, decoding, image reconstruction, image resolution, Streaming media BibRef

Pavez, E., Ortega, A., Mukherjee, D.,
Learning separable transforms by inverse covariance estimation,
ICIP17(285-289)
IEEE DOI 1803
Covariance matrices, Discrete cosine transforms, Encoding, Estimation, Image coding, video coding BibRef

Shen, H., Pan, W.D.[W. David],
Predictive lossless compression of regions of interest in hyperspectral image via Maximum Correntropy Criterion based Least Mean Square learning,
ICIP16(2182-2186)
IEEE DOI 1610
Data communication BibRef

Quijas, J., Fuentes, O.,
Removing JPEG blocking artifacts using machine learning,
Southwest14(77-80)
IEEE DOI 1406
data compression BibRef

Zhan, X.[Xin], Zhang, R.[Rong], Yin, D.[Dong], Hu, A.Z.[An-Zhou], Hu, W.L.[Wen-Long],
Remote sensing image compression based on double-sparsity dictionary learning and universal trellis coded quantization,
ICIP13(1665-1669)
IEEE DOI 1402
Dictionary learning BibRef

Sun, X.Y.[Xiao-Yan], Wu, F.[Feng],
Classified patch learning for spatially scalable video coding,
ICIP09(2301-2304).
IEEE DOI 0911
BibRef

He, X.F.[Xiao-Fei], Ji, M.[Ming], Bao, H.J.[Hu-Jun],
A unified active and semi-supervised learning framework for image compression,
CVPR09(65-72).
IEEE DOI 0906
Learn which pixels predict the color for others. BibRef

Lampert, C.H.[Christoph H.],
Machine Learning for Video Compression: Macroblock Mode Decision,
ICPR06(I: 936-940).
IEEE DOI 0609
BibRef

Simard, P.Y., Burges, C.J.C., Steinkraus, D., Malvar, H.S.,
Image compression with on-line and off-line learning,
ICIP03(II: 259-262).
IEEE DOI 0312
BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Motion Coding, Video Coding, Evaluations, Surveys .


Last update:Nov 30, 2023 at 15:51:27