CVPR CLIC 2018 and Image-Compression-and-Video-Coding Summary [Web]

CVPR 2018- Workshop and Challenge on Learned Image Compression [Web]

• An Autoencoder-based Learned Image Compressor: Description of Challenge Proposal by NCTU

• Autoencoders with Variable Sized Latent Vector for Image Compression

• An Implementation of Picture Compression with A CNN-based Auto-encoder

• Block-optimized Variable Bit Rate Neural Image Compression

• BlockCNN: A Deep Network for Artifact Removal and Image Compression

• CNN-Optimized Image Compression with Uncertainty based Resource Allocation

• Compression artifact removal using multi-scale reshuffling convolutional network

• Combine Traditional Compression MethodWith Convolutional Neural Networks

• Deep Image Compression via End-to-End Learning

• Decoder Side Image Quality Enhancement exploiting Inter-channel Correlation in a 3-stage CNN: Submission to CLIC 2018

• Extreme Learned Image Compression with GANs

• Fully Convolutional Model for Variable Bit Length and Lossy High Density Compression of Mammograms

• Image compression with xvc

• Joint denoising and decompression using CNN regularization

• Learned Compression Artifact Removal by Deep Residual Networks

• Learning Compressible 360? Video Isomers

• Perceptually optimized low bit-rate image encoding

• Performance Comparison of Convolutional AutoEncoders, Generative Adversarial Networks and Super-Resolution for Image Compression

• Variational Autoencoder for Low Bit-rate Image Compression

• Wide-activated Deep Residual Networks based Restoration for BPG-compressed Images

• YASO

Image-Compression-and-Video-Coding

(Some summary comes from here [[Web]] (https://github.com/flyywh/Image-compression-and-video-coding)

• Compressive Autoencoders [Web] [PDF]

  • Lossy Image Compression with Compressive Autoencoders (ICLR 2017), Lucas Theis, Wenzhe Shi, Andrew Cunningham.

• End-to-end Compression [Web] [PDF]

  • End-to-end Optimized Image Compression (ICLR 2017), Ball茅, Laparra & Simoncelli.

• Recurrent Neural Networks [Web] [PDF]

  • Full Resolution Image Compression with Recurrent Neural Networks (Arxiv 2016), George Toderici, Damien Vincent, Nick Johnston, Sung Jin Hwang, David Minnen, Joel Shor, Michele Covell.

• CAS-CNN [Web] [PDF]

  • CAS-CNN: A Deep Convolutional Neural Network for Image Compression Artifact Suppression (Arxiv 2016), Lukas Cavigelli, Pascal Hager, Luca Benini.

• Semantic Perceptual Image Compression [Web] [PDF]

  • Semantic Perceptual Image Compression using Deep Convolution Networks (Arxiv 2016), A Prakash, N Moran, S Garber, A DiLillo, J Storer.

• Generative Compression [Web] [PDF]

  • Generative Compression (Arxiv 2017), Shibani Santurkar, David Budden, Nir Shavit.

• Semantic Perceptual Image Compression [Web] [PDF]

  • Semantic Perceptual Image Compression using Deep Convolution Networks (Arxiv 2016), A Prakash, N Moran, S Garber, A DiLillo, J Storer.

• Nonlinear Transform Codes [Web] [PDF]

  • End-to-end optimization of nonlinear transform codes for perceptual quality (PCS 2016), Johannes Ball茅, Valero Laparra, Eero P. Simoncelli.

• Conceptual Compression [Web] [PDF]

  • Towards Conceptual Compression (NIPS 2016), Karol Gregor, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, Daan Wierstra.

• Auto-encoders compression [Web] [PDF]

  • Auto-encoders: reconstruction versus compression (Arxiv 2014), Yann Ollivier.

• Lightweight Lossy Compression [Web] [PDF]

  • Lightweight Lossy Compression of Biometric Patterns via Denoising Autoencoders (IEEE SPL 2015), Davide Del Testa, Michele Rossi.

• Variable Rate Image Compression [Web] [PDF]

  • Variable Rate Image Compression with Recurrent Neural Networks (Arxiv 2015), George Toderici, Sean M. O'Malley, Sung Jin Hwang, Damien Vincent, David Minnen, Shumeet Baluja, Michele Covell, Rahul Sukthankar.

• Priming and Spatially Adaptive Bit Rates Compression[Web] [PDF]

  • Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networks (Arxiv 2017), Nick Johnston, Damien Vincent, David Minnen, Michele Covell, Saurabh Singh, Troy Chinen, Sung Jin Hwang, Joel Shor, George Toderici.

• Learning Convolutional Networks for Content-weighted Image Compression[Web] [PDF]

  • Learning Convolutional Networks for Content-weighted Image Compression (Arxiv 2017), Mu Li, Wangmeng Zuo, Shuhang Gu, Debin Zhao, David Zhang.

• Convolutional Neural Network-Based Block Up-sampling for Intra Frame Coding[Web] [PDF]

  • Convolutional Neural Network-Based Block Up-sampling for Intra Frame Coding (TCSVT 2017), Yue Li, Dong Liu, Houqiang Li, Li Li, and Feng Wu.

• A Convolutional Neural Network Approach for Half-Pel Interpolation in Video Coding[Web] [PDF]

  • Convolutional Neural Network-Based Block Up-sampling for Intra Frame Coding (Arxiv 2017), Ning Yan, Dong Liu, Houqiang Li, and Feng Wu.

• Soft-to-Hard Vector Quantization for End-to-End Learned Compression of mages and Neural Networks[Web] [PDF]

  • Soft-to-Hard Vector Quantization for End-to-End Learned Compression of mages and Neural Networks (Arxiv 2017), Eirikur Agustsson, Fabian Mentzer, Michael Tschannen, Lukas Cavigelli, Radu Timofte, Luca Benini, Luc Van Gool.

• DC Coefficient Estimation [PDF]

  • DC Coefficient Estimation of Intra-Predicted Residuals in HEVC (TCSVT 2017), Chen Chen, Zexiang Miao, Xiandong Meng, Shuyuan Zhu, Bing Zeng.

• Variable Block-Sized Signal Dependent Transform [PDF]

  • Variable Block-Sized Signal Dependent Transform for Video Coding (TCSVT 2017), Cuiling Lan, Jizheng Xu, Wenjun Zeng, Guangming Shi, Feng Wu.

• Codes + CNN [PDF]

  • An End-to-End Compression Framework Based on Convolutional Neural Networks (TCSVT 2017), Feng Jiang, Wen Tao, Shaohui Liu, Jie Ren, Xun Guo, Debin Zhao.

• Virtual codec [PDF]

  • Learning a Virtual Codec Based on Deep Convolutional Neural Network to Compress Image, Lijun Zhao, Huihui Bai, Anhong Wang, Yao Zhao

• SCIC and DNNC[PDF]

  • Virtual Codec Supervised Re-Sampling Network for Image Compression, Lijun Zhao, Huihui Bai, Anhong Wang, Yao Zhao

• MDCNN [Web] [PDF]

  • Multiple Description Convolutional Neural Networks for Image Compression, Lijun Zhao, Huihui Bai, Anhong Wang, Yao Zhao