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Yu Zhu

Institute of Automation, Chinese Academy of Sciences

10 papers hereh-index 10373 citations17 works total

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

author position
  • first author1
  • middle author6

Across the 7 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • eess.IV3
  • q-bio.NC2
  • cs.LG1
  • stat.ML1
affiliations
  • Institute of Automation, Chinese Academy of Sciences
HomepageORCID 0000-0001-8836-7939
same name
  • Yu Zhu — 15 papers, h 14
  • Yu Zhu — 9 papers, h 6
  • Yu Zhu — 8 papers, h 17
  • Yu Zhu — 8 papers, h 2
  • Yu Zhu — 6 papers, h 15
  • Yu Zhu — 6 papers, h 5

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
20202024
most citedAIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results

16 citations · 52 across the 9 of their papers we have counts for

collaborators
Showing 2022Show all

3 papers · 1 filter

eess.IV2022★ 1 cited

Reversed Image Signal Processing and RAW Reconstruction. AIM 2022 Challenge Report

Marcos V. Conde, Radu Timofte, Yibin Huang +40

Cameras capture sensor RAW images and transform them into pleasant RGB images, suitable for the human eyes, using their integrated Image Signal Processor (ISP). Numerous low-level…

cs.CV2022★ 3 cited

AIM 2022 Challenge on Instagram Filter Removal: Methods and Results

Furkan Kınlı, Sami Menteş, Barış Özcan +30

This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations,…

eess.IV2022★ 16 cited

AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results

Ren Yang, Radu Timofte, Xin Li +49

This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compress…

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