34 citations · 60 across the 9 of their papers we have counts for
12 papers
Dual-Latent Collaborative Decoding for Fidelity-Perception Balanced Image Compression
Qi Mao, Zijian Wang, Zhengxue Cheng +2
Learned image compression (LIC) increasingly requires reconstructions that balance distortion fidelity and perceptual realism across a wide range of bitrates. However, most existin…
End-to-end Learned Image Compression with Fixed Point Weight Quantization
Heming Sun, Zhengxue Cheng, Masaru Takeuchi +1
Learned image compression (LIC) has reached the traditional hand-crafted methods such as JPEG2000 and BPG in terms of the coding gain. However, the large model size of the network…
Enhanced Intra Prediction for Video Coding by Using Multiple Neural Networks
Heming Sun, Zhengxue Cheng, Masaru Takeuchi +1
This paper enhances the intra prediction by using multiple neural network modes (NM). Each NM serves as an end-to-end mapping from the neighboring reference blocks to the current c…
Low Bitrate Image Compression with Discretized Gaussian Mixture Likelihoods
Zhengxue Cheng, Heming Sun, Jiro Katto
In this paper, we provide a detailed description on our submitted method Kattolab to Workshop and Challenge on Learned Image Compression (CLIC) 2020. Our method mainly incorporates…
Learned Lossless Image Compression with a HyperPrior and Discretized Gaussian Mixture Likelihoods
Zhengxue Cheng, Heming Sun, Masaru Takeuchi +1
Lossless image compression is an important task in the field of multimedia communication. Traditional image codecs typically support lossless mode, such as WebP, JPEG2000, FLIF. Re…
Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modules
Zhengxue Cheng, Heming Sun, Masaru Takeuchi +1
Image compression is a fundamental research field and many well-known compression standards have been developed for many decades. Recently, learned compression methods exhibit a fa…