75 citations · 195 across the 21 of their papers we have counts for
21 papers
Asymmetric Learned Image Compression with Multi-Scale Residual Block, Importance Map, and Post-Quantization Filtering
Haisheng Fu, Feng Liang, Jie Liang +3
Recently, deep learning-based image compression has made signifcant progresses, and has achieved better ratedistortion (R-D) performance than the latest traditional method, H.266/V…
Auto-Weighted Layer Representation Based View Synthesis Distortion Estimation for 3-D Video Coding
Jian Jin, Xingxing Zhang, Lili Meng +4
Recently, various view synthesis distortion estimation models have been studied to better serve for 3-D video coding. However, they can hardly model the relationship quantitatively…
Learned Image Compression with Gaussian-Laplacian-Logistic Mixture Model and Concatenated Residual Modules
Haisheng Fu, Feng Liang, Jianping Lin +7
Recently deep learning-based image compression methods have achieved significant achievements and gradually outperformed traditional approaches including the latest standard Versat…
Learned Multi-Resolution Variable-Rate Image Compression with Octave-based Residual Blocks
Mohammad Akbari, Jie Liang, Jingning Han +1
Recently deep learning-based image compression has shown the potential to outperform traditional codecs. However, most existing methods train multiple networks for multiple bit rat…
Learned Variable-Rate Multi-Frequency Image Compression using Modulated Generalized Octave Convolution
Jianping Lin, Mohammad Akbari, Haisheng Fu +7
In this proposal, we design a learned multi-frequency image compression approach that uses generalized octave convolutions to factorize the latent representations into high-frequen…
Deep Learning-based Image Compression with Trellis Coded Quantization
Binglin Li, Mohammad Akbari, Jie Liang +1
Recently many works attempt to develop image compression models based on deep learning architectures, where the uniform scalar quantizer (SQ) is commonly applied to the feature map…