4 citations · 9 across the 5 of their papers we have counts for
3 papers · 1 filter
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…