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W. Lian

4 papers hereh-index 498 citations6 works total

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

author position
  • middle author2
  • last author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • eess.IV2
same name
  • W. Lian — 11 papers, h 9
  • W. Lian — 4 papers, h 8
  • W. Lian — 3 papers, h 15
  • W. Lian — 1 paper, h 1

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

most citedNTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results

3 citations · 5 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2024★ 3 cited

NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results

Xiaoning Liu, Zongwei Wu, Ao Li +109

This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results. The aim of this challenge is to discover an effective netw…

cs.CV2024

Equipping Diffusion Models with Differentiable Spatial Entropy for Low-Light Image Enhancement

Wenyi Lian, Wenjing Lian, Ziwei Luo

Image restoration, which aims to recover high-quality images from their corrupted counterparts, often faces the challenge of being an ill-posed problem that allows multiple solutio…

eess.IV2022

Power Efficient Video Super-Resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 challenge: Report

Andrey Ignatov, Radu Timofte, Cheng-Ming Chiang +50

Video super-resolution is one of the most popular tasks on mobile devices, being widely used for an automatic improvement of low-bitrate and low-resolution video streams. While num…

eess.IV2022★ 2 cited

Sliding Window Recurrent Network for Efficient Video Super-Resolution

Wenyi Lian, Wenjing Lian

Video super-resolution (VSR) is the task of restoring high-resolution frames from a sequence of low-resolution inputs. Different from single image super-resolution, VSR can utilize…

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