28 citations · 89 across the 12 of their papers we have counts for
5 papers · 1 filter
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…
Generalized Octave Convolutions for Learned Multi-Frequency Image Compression
Mohammad Akbari, Jie Liang, Jingning Han +1
Learned image compression has recently shown the potential to outperform the standard codecs. State-of-the-art rate-distortion (R-D) performance has been achieved by context-adapti…
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…
Learned Variable-Rate Image Compression with Residual Divisive Normalization
Mohammad Akbari, Jie Liang, Jingning Han +1
Recently it has been shown that deep learning-based image compression has shown the potential to outperform traditional codecs. However, most existing methods train multiple networ…
Improved Hybrid Layered Image Compression using Deep Learning and Traditional Codecs
Haisheng Fu, Feng Liang, Bo Lei +5
Recently deep learning-based methods have been applied in image compression and achieved many promising results. In this paper, we propose an improved hybrid layered image compress…