Recent papers and codes related to deep learning/deep neural network based image compression and video coding framework.
Recent papers and codes related to deep learning/deep neural network based image compression and video coding framework.
[Macau University] Yumo Zhang, Zhanchuan Cai , Senior Member, IEEE, and Gangqiang Xiong: A New Image Compression Algorithm Based on Non-Uniform Partition and U-System. TMM 2021. [paper]
[Tohoku University] Shoma Iwai, Tomo Miyazaki, Yoshihiro Sugaya, and Shinichiro Omachi: Fidelity-Controllable Extreme Image Compression with Generative Adversarial Networks. ICPR 2021. [paper]
[Nanjing University] Tong Chen, Haojie Liu, Zhan Ma, Qiu Shen, Xun Cao, and Yao Wang: End-to-End Learnt Image Compression via Non-Local Attention Optimization and Improved Context Modeling. TIP 2021. [paper]
[USTC] Yefei Wang, Dong Liu, Siwei Ma, Feng Wu, Wen Gao: Ensemble Learning-Based Rate-Distortion Optimization for End-to-End Image Compression. TCSVT 2021. [paper]
[Peking University] Yueyu Hu, Wenhan Yang, Zhan Ma, Jiaying Liu: Learning End-to-End Lossy Image Compression: A Benchmark. TPAMI 2021. [paper]
[SFU] Mohammad Akbari, Jie Liang, Jingning Han, Chengjie Tu: Learned Multi-Resolution Variable-Rate Image Compression with Octave-based Residual Blocks. TMM 2021. [paper]
[USTC] Zongyu Guo, Zhizheng Zhang, Runsen Feng and Zhibo Chen: Causal Contextual Prediction for Learned Image Compression. TCSVT 2021. [paper]
[Sejong University] Khawar Islam, Dang Lien Minh, Sujin Lee, Hyeonjoon Moon: Image Compression with Recurrent Neural Network and Generalized Divisive Normalization. CVPR 2021. [paper]
[USTC] Haichuan Ma, Dong Liu, Cunhui Dong, Li Li, Feng Wu: End-to-End Image Compression with Probabilistic Decoding. [paper]
[SenseTime Research] Baocheng Sun, Meng Gu, Dailan He, Tongda Xu, Yan Wang, Hongwei Qin: HLIC: Harmonizing Optimization Metrics in Learned Image Compression by Reinforcement Learning. [paper]
[Seoul National University] Myungseo Song, Jinyoung Choi, Bohyung Han: Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform. ICCV 2021. [paper]
[Northwestern Polytechnical University] Fei Yang, Luis Herranz, Yongmei Cheng, Mikhail G. Mozerov: Slimmable Compressive Autoencoders for Practical Neural Image Compression. CVPR 2021. [paper]
[SenseTime Research] Dailan He, Yaoyan Zheng, Baocheng Sun, Yan Wang, Hongwei Qin: Checkerboard Context Model for Efficient Learned Image Compression. CVPR 2021. [paper]
[Peng Cheng Lab] Yuanchao Bai, Xianming Liu, Wangmeng Zuo, Yaowei Wang, Xiangyang Ji: Learning Scalable ℓ∞-constrained Near-lossless Image Compression via Joint Lossy Image and Residual Compression. CVPR 2021. [paper]
[SJTU] Xi Zhang, Xiaolin Wu: Attention-guided Image Compression by Deep Reconstruction of Compressive Sensed Saliency Skeleton. CVPR 2021. [paper]
[HIT] Yang Wang, Xiaopeng Fan, Ruiqin Xiong, Debin Zhao, Wen Gao: Neural Network-based Enhancement to Inter Prediction for Video Coding. TCSVT 2021. [paper]
[BBC Research] Marc Górriz Blanch, Saverio Blasi, Alan F. Smeaton, Noel E. O’Connor, and Marta Mrak: Neural Network-based Enhancement to Inter Prediction for Video Coding. JSTSP 2021. [paper]
[Microsoft Research Asia] Jiahao Li, Bin Li, Yan Lu: Deep Contextual Video Compression. [paper]
[HIT] Hengyu Man, Xiaopeng Fan, Ruiqin Xiong, Debin Zhao: Data Clustering-Driven Neural Network for Intra Prediction. [paper]
[iSIZE] Aaron Chadha, Yiannis Andreopoulos: Deep Perceptual Preprocessing for Video Coding. CVPR 2021. [paper]
[Hosei University] Chi D. K. Pham, Chen Fu, Jinjia Zhou: Deep Learning Based Spatial-Temporal In-Loop Filtering for Versatile Video Coding. CVPR 2021. [paper]
[Qualcomm Technologies] Hilmi E. Egilmez, Ankitesh K. Singh, Muhammed Coban, Marta Karczewicz, Yinhao Zhu, Yang Yang, Amir Said, Taco S. Cohen: Transform Network Architectures for Deep Learning based End-to-End Image/Video Coding in Subsampled Color Spaces. [paper]
[Nanjing University] Ming Lu and Zhan Ma: High-Efficiency Lossy Image Coding Through Adaptive Neighborhood Information Aggregation. [paper]
[New York University] Jiuhong Xiao, Lavisha Aggarwal, Prithviraj Banerjee, Manoj Aggarwal, and Gerard Medioni: Identity Preserving Loss for Learned Image Compression. [paper]
[University of Texas] Li-Heng Chen, Christos G. Bampis, Zhi Li, Lukas Krasula, and Alan C. Bovik: Estimating the Resize Parameter in End-to-end Learned Image Compression. [paper]
[UCAS] Renjie Zou, Chunfeng Song and Zhaoxiang Zhang: The Devil Is in the Details: Window-based Attention for Image Compression. [paper]
[UESTC] Xiaosu Zhu, Jingkuan Song, Lianli Gao Feng Zheng Heng Tao Shen: Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression. [paper]
[Technical University of Munich] A. Burakhan Koyuncu, Han Gao, Eckehard Steinbach: contextformer: A Transformer with spatio-channel attention for context modeling in learned image compression. [paper]
[Peking University] Dezhao Wang Wenhan Yang Yueyu Hu Jiaying Liu: Neural Data-Dependent Transform for Learned Image Compression. [paper]
[Tsinghua University] Dailan He1, Ziming Yang, Weikun Peng, Rui Ma, Hongwei Qin, Yan Wang: ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding. [paper]
[Peking University] Yi Ma, Yongqi Zhai, and Ronggang Wang: DeepFGS: Fine-Grained Scalable Coding for Learned Image Compression. [paper]
[Friedrich-Alexander University] Fabian Brand, Kristian Fischer, Alexander Kopte, and Andre Kaup: Learning True Rate-Distortion-Optimization for End-To-End Image Compression. [paper]
[Alibaba Group] Yichen Qian, Ming Lin, Xiuyu Sun: EnTroformer: A Transformer-based Entropy Model for Learned Image Compression. [paper]
[SenseTime Research] Dailan He, Ziming Yang, Yuan Chen, Qi Zhang, Hongwei Qin, Yan Wang: Post-Training Quantization for Cross-Platform Learned Image Compression. [paper]
[Vrije Universiteit Amsterdam] Yura Perugachi-Diaz, Guillaume Sautiere, Davide Abati, Yang Yang: Region-of-Interest Based Neural Video Compression. [paper]
[Nanjing University of Aeronautics and Astronautics] Haoyue Tian, Pan Gao, Ran Wei, Manoranjan Paul: Dilated Convolutional Neural Network-based Deep Reference Picture Generation for video compression. [paper]
[Koç University] M. Akın Yılmaz, and A. Murat Tekalp: End-to-End Rate-Distortion Optimized Learned Hierarchical Bi-Directional Video Compression. TIP 2022. [paper]
[Nanjing University] Dandan Ding , Xiang Gao, Chenran Tang, and Zhan Ma: Neural Reference Synthesis for Inter Frame Coding. TIP 2022. [paper]