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Learned Video Compression via Joint Spatial-Temporal Correlation Exploration [article]

Haojie Liu, Han shen, Lichao Huang, Ming Lu, Tong Chen, Zhan Ma
2019 arXiv   pre-print
We evaluate our approach for the low-delay scenario with High-Efficiency Video Coding (H.265/HEVC), H.264/AVC and another learned video compression method, following the common test settings.  ...  Traditional video compression technologies have been developed over decades in pursuit of higher coding efficiency. Efficient temporal information representation plays a key role in video coding.  ...  And then we joint train video compression framework on Vimeo 90k (Xue et al. 2019) which is a widely used dataset for low-level video processing tasks.  ... 
arXiv:1912.06348v1 fatcat:h6chbcl52nbwtbpx6hrrzj7fme

Learned Video Compression via Joint Spatial-Temporal Correlation Exploration

Haojie Liu, Han Shen, Lichao Huang, Ming Lu, Tong Chen, Zhan Ma
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
We evaluate our approach for the low-delay scenario with High-Efficiency Video Coding (H.265/HEVC), H.264/AVC and another learned video compression method, following the common test settings.  ...  Traditional video compression technologies have been developed over decades in pursuit of higher coding efficiency. Efficient temporal information representation plays a key role in video coding.  ...  And then we joint train video compression framework on Vimeo 90k (Xue et al. 2019) which is a widely used dataset for low-level video processing tasks.  ... 
doi:10.1609/aaai.v34i07.6825 fatcat:naduixdarnfy3ebtcw55ht2h5e

An Emerging Coding Paradigm VCM: A Scalable Coding Approach Beyond Feature and Signal [article]

Sifeng Xia, Kunchangtai Liang, Wenhan Yang, Ling-Yu Duan, Jiaying Liu
2020 arXiv   pre-print
Specifically, we employ a conditional deep generation network to reconstruct video frames with the guidance of learned motion pattern.  ...  performance over highly compressed videos (9.4% gain in recognition accuracy), which showcases a promising paradigm of coding signal for both human and machine vision.  ...  JOINT COMPRESSION OF FEATURES AND VIDEOS Given a video sequence I = {I 1 , I 2 , ..., I N } where N indicates the frame number, it is necessary to compress I for transmission and storage.  ... 
arXiv:2001.03004v1 fatcat:5wkilmqmsvhhvet2xvoto7fwui

Semantically Video Coding: Instill Static-Dynamic Clues into Structured Bitstream for AI Tasks [article]

Xin Jin, Ruoyu Feng, Simeng Sun, Runsen Feng, Tianyu He, Zhibo Chen
2022 arXiv   pre-print
Video signals contain more rich dynamic motion information and exist more redundancy due to the similarity between adjacent frames.  ...  This avoids the full bitstream decompression and thus significantly saves bitrate/bandwidth consumption for intelligent analytics.  ...  For the pretraining of our p-frame codec, we first fix the weights of Residual Compression (RC) network for joint training.  ... 
arXiv:2201.10162v2 fatcat:erjq25be3bbgzkled3bf2s34fi

Remote Heart Rate Measurement From Highly Compressed Facial Videos: An End-to-End Deep Learning Solution With Video Enhancement

Zitong Yu, Wei Peng, Xiaobai Li, Xiaopeng Hong, Guoying Zhao
2019 2019 IEEE/CVF International Conference on Computer Vision (ICCV)  
The rPPGNet can work on its own for robust rPPG measurement, and the STVEN network can be added and jointly trained to further boost the performance especially on highly compressed videos.  ...  The method includes two parts: 1) a Spatio-Temporal Video Enhancement Network (STVEN) for video enhancement, and 2) an rPPG network (rPPGNet) for rPPG signal recovery.  ...  In all, the joint cost function L joint for STVEN can be formulated as L joint = L rP P GN et + εL p + ρL ST V EN , (10) here ε and ρ are hyper-parameters.  ... 
doi:10.1109/iccv.2019.00024 dblp:conf/iccv/YuPLHZ19 fatcat:oixvacn2l5dwbahjfjkxubhlsq

Multi-frame Joint Enhancement for Early Interlaced Videos [article]

Yang Zhao, Yanbo Ma, Yuan Chen, Wei Jia, Ronggang Wang, Xiaoping Liu
2021 arXiv   pre-print
Early interlaced videos usually contain multiple and interlacing and complex compression artifacts, which significantly reduce the visual quality.  ...  Traditional methods mainly focus on simple interlacing mechanism, and cannot deal with the complex artifacts in real-world early videos.  ...  -4K(50P), demonstrate that the proposed model is suitable for the joint problem of deinterlacing, compression artifacts removal, video super-resolution and double frame rate.  ... 
arXiv:2109.14151v1 fatcat:eb3ertaaubcjja3c2icxwjb7tm

Content Adaptive and Error Propagation Aware Deep Video Compression [article]

Guo Lu, Chunlei Cai, Xiaoyun Zhang, Li Chen, Wanli Ouyang, Dong Xu, Zhiyong Gao
2020 arXiv   pre-print
Specifically, our method employs a joint training strategy by considering the compression performance of multiple consecutive frames instead of a single frame.  ...  Recently, learning based video compression methods attract increasing attention.  ...  [14] are based on frame interpolation and designed for B-frame video compression, while the methods in [19, 16] are for P-frame based video compression.  ... 
arXiv:2003.11282v1 fatcat:5isttklczzfjpkuvm6cx4yd6vm

AlphaVC: High-Performance and Efficient Learned Video Compression [article]

Yibo Shi, Yunying Ge, Jing Wang, Jue Mao
2022 arXiv   pre-print
Recently, learned video compression has drawn lots of attention and show a rapid development trend with promising results.  ...  With these powerful techniques, this paper proposes AlphaVC, a high-performance and efficient learned video compression scheme.  ...  We introduce a new type of frame named conditional-I frame (cI-frame) and propose a new coding mode for learned video compression.  ... 
arXiv:2207.14678v1 fatcat:rxn2zvtpbzbhfhgjykybh6ipam

Neural Video Coding using Multiscale Motion Compensation and Spatiotemporal Context Model [article]

Haojie Liu, Ming Lu, Zhan Ma, Fan Wang, Zhihuang Xie, Xun Cao, Yao Wang
2020 arXiv   pre-print
global and local information, and 4) we introduce multi-module optimization and a multi-frame training strategy to minimize the temporal error propagation among P-frames.  ...  NVC is evaluated for the low-delay causal settings and compared with H.265/HEVC, H.264/AVC and the other learnt video compression methods following the common test conditions, demonstrating consistent  ...  Either separable or joint optimization of flow derivation and compression can be applied for such two-stage approach.  ... 
arXiv:2007.04574v1 fatcat:gc5lnxixnvemdildw246wzaduq

Generative Memorize-Then-Recall framework for low bit-rate Surveillance Video Compression [article]

Yaojun Wu, Tianyu He, Zhibo Chen
2020 arXiv   pre-print
In this paper, we figure out this issue by disentangling surveillance video into the structure of a global spatio-temporal feature (memory) for Group of Picture (GoP) and skeleton for each frame (clue)  ...  with the latest video compression standard H.265.  ...  ACKNOWLEDGMENT This work was supported in part by NSFC under Grant U1908209, 61571413, 61632001 and the National Key Research and Development Program of China 2018AAA0101400.  ... 
arXiv:1912.12847v3 fatcat:nfy5qwff25e4nm2mby4ip62zze

Learning-based multiview video coding

Baochun Bai, Li Cheng, Cheng Lei, Pierre Boulanger, Janelle Harms
2009 2009 Picture Coding Symposium  
We model the multiview video compression problem as a semi-supervised learning problem and design sophisticated mechanisms to achieve high compression efficiency.  ...  Index Terms-joint multiview video coding, semi-supervised learning, multiview video plus depth format, 3D TV, H.264  ...  For example, the Joint Video Team (JVT) of MPEG and ITU-T is now developing a Joint Multiview Video Model (JMVM) which is based on the H.264 hybrid video coding standard [2] .  ... 
doi:10.1109/pcs.2009.5167441 dblp:conf/pcs/BaiCLBH09 fatcat:oqt4rkqo25hiznvg7p4n5ten3a

Video Compression With Rate-Distortion Autoencoders [article]

Amirhossein Habibian, Ties van Rozendaal, Jakub M. Tomczak, Taco S. Cohen
2019 arXiv   pre-print
In this paper we present a a deep generative model for lossy video compression.  ...  Despite its simplicity, we find that our method outperforms the state-of-the-art learned video compression networks based on motion compensation or interpolation.  ...  can be claimed that these learned video compression methods suppress traditional codecs under optimal settings.  ... 
arXiv:1908.05717v2 fatcat:ntnd7l5b3ze73ogdxcajck65cy

Conditional Entropy Coding for Efficient Video Compression [article]

Jerry Liu, Shenlong Wang, Wei-Chiu Ma, Meet Shah, Rui Hu, Pranaab Dhawan, Raquel Urtasun
2020 arXiv   pre-print
We propose a very simple and efficient video compression framework that only focuses on modeling the conditional entropy between frames.  ...  We first show that a simple architecture modeling the entropy between the image latent codes is as competitive as other neural video compression works and video codecs while being much faster and easier  ...  MS-SSIM dB learning-based generalizations of the traditional video compression techniques of motion-compensation, frame interpolation and residual coding.  ... 
arXiv:2008.09180v1 fatcat:ypfuqs2prvcspb6zvmb56zoibu

Spatio-Temporal Deformable Convolution for Compressed Video Quality Enhancement

Jianing Deng, Li Wang, Shiliang Pu, Cheng Zhuo
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
Recent years have witnessed remarkable success of deep learning methods in quality enhancement for compressed video.  ...  In addition, optical flow estimation for consecutive frames is generally conducted in a pairwise manner, which is computational expensive and inefficient.  ...  This work was partially supported by NSFC (Grant No.61601406, No.61974133), and Guangdong Province (Grant No.2018B030338001).  ... 
doi:10.1609/aaai.v34i07.6697 fatcat:cn5jy5kn45gglbmeut46nkpvom

Neural Video Compression using Spatio-Temporal Priors [article]

Haojie Liu, Tong Chen, Ming Lu, Qiu Shen, Zhan Ma
2019 arXiv   pre-print
In this work, we propose a neural video compression framework, leveraging the spatial and temporal priors, independently and jointly to exploit the correlations in intra texture, optical flow based temporal  ...  The pursuit of higher compression efficiency continuously drives the advances of video coding technologies.  ...  To well balance the efficiency of temporal information learning and training memory consumption, we have enrolled 5 frames to train the video compression framework and shared the weights for the rest in  ... 
arXiv:1902.07383v2 fatcat:brynmcohtzdtdo3nyymhsshubi
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