44 citations · 118 across the 12 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…
Dual Learning-based Video Coding with Inception Dense Blocks
Chao Liu, Heming Sun, Junan Chen +5
In this paper, a dual learning-based method in intra coding is introduced for PCS Grand Challenge. This method is mainly composed of two parts: intra prediction and reconstruction…
Learning Image and Video Compression through Spatial-Temporal Energy Compaction
Zhengxue Cheng, Heming Sun, Masaru Takeuchi +1
Compression has been an important research topic for many decades, to produce a significant impact on data transmission and storage. Recent advances have shown a great potential of…
Deep Residual Learning for Image Compression
Zhengxue Cheng, Heming Sun, Masaru Takeuchi +1
In this paper, we provide a detailed description on our approach designed for CVPR 2019 Workshop and Challenge on Learned Image Compression (CLIC). Our approach mainly consists of…
Perceptual Quality Study on Deep Learning based Image Compression
Zhengxue Cheng, Pinar Akyazi, Heming Sun +2
Recently deep learning based image compression has made rapid advances with promising results based on objective quality metrics. However, a rigorous subjective quality evaluation…
Performance Comparison of Convolutional AutoEncoders, Generative Adversarial Networks and Super-Resolution for Image Compression
Zhengxue Cheng, Heming Sun, Masaru Takeuchi +1
Image compression has been investigated for many decades. Recently, deep learning approaches have achieved a great success in many computer vision tasks, and are gradually used in…
Deep Convolutional AutoEncoder-based Lossy Image Compression
Zhengxue Cheng, Heming Sun, Masaru Takeuchi +1
Image compression has been investigated as a fundamental research topic for many decades. Recently, deep learning has achieved great success in many computer vision tasks, and is g…