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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 2021Show all

4 papers · 1 filter

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…

cs.CV2021

Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation

Rui Peng, Ronggang Wang, Yawen Lai +2

Self-supervised methods play an increasingly important role in monocular depth estimation due to their great potential and low annotation cost. To close the gap with supervised met…

cs.CV2021★ 1 cited

Super-Resolving Compressed Video in Coding Chain

Dewang Hou, Yang Zhao, Yuyao Ye +3

Scaling and lossy coding are widely used in video transmission and storage. Previous methods for enhancing the resolution of such videos often ignore the inherent interference betw…

cs.CV2021★ 95 cited

COLA-Net: Collaborative Attention Network for Image Restoration

Chong Mou, Jian Zhang, Xiaopeng Fan +2

Local and non-local attention-based methods have been well studied in various image restoration tasks while leading to promising performance. However, most of the existing methods…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.