activity
20172024
most citedMLIC: Multi-Reference Entropy Model for Learned Image Compression

118 citations · 277 across the 12 of their papers we have counts for

collaborators

13 papers

eess.IV2024

DeepFGS: Fine-Grained Scalable Coding for Learned Image Compression

Yongqi Zhai, Yi Ma, Luyang Tang +2

Scalable coding, which can adapt to channel bandwidth variation, performs well in today's complex network environment. However, most existing scalable compression methods face two…

eess.IV2022★ 118 cited

MLIC: Multi-Reference Entropy Model for Learned Image Compression

Wei Jiang, Jiayu Yang, Yongqi Zhai +3

Recently, learned image compression has achieved remarkable performance. The entropy model, which estimates the distribution of the latent representation, plays a crucial role in b…

cs.CV2022

Improving Multi-generation Robustness of Learned Image Compression

Litian Li, Zheng Yang, Ronggang Wang

Benefit from flexible network designs and end-to-end joint optimization approach, learned image compression (LIC) has demonstrated excellent coding performance and practical feasib…

cs.MM2022★ 48 cited

Consistent Quality Oriented Rate Control in HEVC via Balancing Intra and Inter Frame Coding

Wei Gao, Qiuping Jiang, Ronggang Wang +3

Consistent quality oriented rate control in video coding has attracted much more attention. However, the existing efforts only focus on decreasing variations between every two adja…

eess.IV2022★ 7 cited

DeepFGS: Fine-Grained Scalable Coding for Learned Image Compression

Yi Ma, Yongqi Zhai, Ronggang Wang

Scalable coding, which can adapt to channel bandwidth variation, performs well in today's complex network environment. However, the existing scalable compression methods face two c…

eess.IV2021★ 6 cited

Multi-frame Joint Enhancement for Early Interlaced Videos

Yang Zhao, Yanbo Ma, Yuan Chen +3

Early interlaced videos usually contain multiple and interlacing and complex compression artifacts, which significantly reduce the visual quality. Although the high-definition reco…