activity
20182026
most citedGeneralized Octave Convolutions for Learned Multi-Frequency Image Compression

21 citations · 57 across the 12 of their papers we have counts for

collaborators

13 papers

eess.IV2026

Transform and Entropy Coding in AV2

Alican Nalci, Hilmi E. Egilmez, Madhu P. Krishnan +21

AV2 is the successor to the AV1 video coding standard developed by the Alliance for Open Media (AOMedia). Its primary objective is to deliver substantial compression gains and subj…

cs.CV2023

ROI-based Deep Image Compression with Swin Transformers

Binglin Li, Jie Liang, Haisheng Fu +1

Encoding the Region Of Interest (ROI) with better quality than the background has many applications including video conferencing systems, video surveillance and object-oriented vis…

eess.IV2022

Multi-rate adaptive transform coding for video compression

Lyndon R. Duong, Bohan Li, Cheng Chen +1

Contemporary lossy image and video coding standards rely on transform coding, the process through which pixels are mapped to an alternative representation to facilitate efficient d…

eess.IV2022

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…

eess.IV2022★ 13 cited

MuZero with Self-competition for Rate Control in VP9 Video Compression

Amol Mandhane, Anton Zhernov, Maribeth Rauh +16

Video streaming usage has seen a significant rise as entertainment, education, and business increasingly rely on online video. Optimizing video compression has the potential to inc…

eess.IV2021

A Quantitative Approach To The Temporal Dependency in Video Coding

Jingning Han, Paul Wilkins, Yaowu Xu +1

Motion compensated prediction is central to the efficiency of video compression. Its predictive coding scheme propagates the quantization distortion through the prediction chain an…

eess.IV2021★ 14 cited

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…

cs.CV2020

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…

cs.LG2020

Neural Rate Control for Video Encoding using Imitation Learning

Hongzi Mao, Chenjie Gu, Miaosen Wang +9

In modern video encoders, rate control is a critical component and has been heavily engineered. It decides how many bits to spend to encode each frame, in order to optimize the rat…

eess.IV2020

A Technical Overview of AV1

Jingning Han, Bohan Li, Debargha Mukherjee +12

The AV1 video compression format is developed by the Alliance for Open Media consortium. It achieves more than 30% reduction in bit-rate compared to its predecessor VP9 for the sam…

eess.IV2020★ 21 cited

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…

eess.IV2019★ 2 cited

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…

cs.CV2018★ 7 cited

DSSLIC: Deep Semantic Segmentation-based Layered Image Compression

Mohammad Akbari, Jie Liang, Jingning Han

Deep learning has revolutionized many computer vision fields in the last few years, including learning-based image compression. In this paper, we propose a deep semantic segmentati…