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Ronggang Wang

13 papers hereh-index 253k citations192 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author6
  • last author6

Across the 12 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CV6
  • eess.IV4
  • cs.MM2
  • cs.AI1
same name
  • Ronggang Wang — 7 papers, h 3
  • Ronggang Wang — 7 papers, h 5
  • Ronggang Wang — 5 papers, h 1
  • Ronggang Wang — 5 papers, h 9
  • Ronggang Wang — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

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

118 citations · 277 across the 13 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

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…

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