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Ding Liu

5 papers here

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

author position
  • first author1
  • middle author2
  • last author1

Across the 4 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • eess.IV1
ORCID 0000-0002-0931-1345
same name
  • Ding Liu — 19 papers, h 39
  • Ding Liu — 1 paper
  • Ding Liu — 1 paper
  • Ding Liu — 1 paper

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
20172023
most citedAIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results

16 citations · 38 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023★ 14 cited

ShadowFormer: Global Context Helps Image Shadow Removal

Lanqing Guo, Siyu Huang, Ding Liu +2

Recent deep learning methods have achieved promising results in image shadow removal. However, most of the existing approaches focus on working locally within shadow and non-shadow…

cs.CV2022★ 6 cited

Dynamic Proposals for Efficient Object Detection

Yiming Cui, Linjie Yang, Ding Liu

Object detection is a basic computer vision task to loccalize and categorize objects in a given image. Most state-of-the-art detection methods utilize a fixed number of proposals a…

cs.CV2022

Boosting Video Super Resolution with Patch-Based Temporal Redundancy Optimization

Yuhao Huang, Hang Dong, Jinshan Pan +5

The success of existing video super-resolution (VSR) algorithms stems mainly exploiting the temporal information from the neighboring frames. However, none of these methods have di…

cs.CV2017★ 2 cited

Learning a Mixture of Deep Networks for Single Image Super-Resolution

Ding Liu, Zhaowen Wang, Nasser Nasrabadi +1

Single image super-resolution (SR) is an ill-posed problem which aims to recover high-resolution (HR) images from their low-resolution (LR) observations. The crux of this problem l…

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