L
Linwei Zhu
Researcher at Chinese Academy of Sciences
Publications - 30
Citations - 338
Linwei Zhu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Encoder & Coding (social sciences). The author has an hindex of 9, co-authored 25 publications receiving 209 citations. Previous affiliations of Linwei Zhu include City University of Hong Kong & Ningbo University.
Papers
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Binary and Multi-Class Learning Based Low Complexity Optimization for HEVC Encoding
TL;DR: A binary and multi-class support vector machine (SVM)-based fast HEVC encoding algorithm that outperforms the state-of-the-art fast coding algorithms in terms of complexity reduction and RD performance.
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Fuzzy SVM-Based Coding Unit Decision in HEVC
TL;DR: A coding unit (CU) decision method based on fuzzy support vector machine (SVM) is proposed for rate-distortion-complexity (RDC) optimization, where the process of CU decision is formulated as a cascaded multi-level classification task.
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Generative adversarial network based intra prediction for video coding
TL;DR: A novel intra prediction method is proposed to improve the video coding performance, in which the generative adversarial network (GAN) is adopted to intelligently remove the spatial redundancy with the inference process.
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Convolutional Neural Network-Based Synthesized View Quality Enhancement for 3D Video Coding
TL;DR: A convolutional neural network (CNN)-based synthesized view quality enhancement method for 3D high efficiency video coding (HEVC) is proposed, which can efficiently eliminate the artifacts in the synthesized image, and reduce 25.9% and 11.7% bit rate, which significantly outperforms the state-of-the-art methods.
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Deep Learning-Based Chroma Prediction for Intra Versatile Video Coding
TL;DR: A deep learning based intra Chroma prediction method, termed as convolutional neural network based chroma prediction (CNNCP), which is incorporated into both video encoder and decoder and can achieve bit rate savings compared with VVC test model version 4.0.