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researcher

Xin Li

4 papers hereh-index 255.6k citations90 works total

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

author position
  • middle author2
  • last author2

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

fields
  • cs.CV2
  • eess.IV2
same name
  • Xin Li — 22 papers, h 21
  • Xin Li — 13 papers, h 19
  • Xin Li — 12 papers, h 23
  • Xin Li — 12 papers
  • Xin Li — 10 papers, h 54
  • Xin Li — 10 papers

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
20182021
most citedDeformable Kernel Convolutional Network for Video Extreme Super-Resolution

1 citations · 1 across the 2 of their papers we have counts for

collaborators

4 papers

eess.IV2021

Searching Efficient Model-guided Deep Network for Image Denoising

Qian Ning, Weisheng Dong, Xin Li +3

Neural architecture search (NAS) has recently reshaped our understanding on various vision tasks. Similar to the success of NAS in high-level vision tasks, it is possible to find a…

cs.CV2020★ 1 cited

Deformable Kernel Convolutional Network for Video Extreme Super-Resolution

Xuan Xu, Xin Xiong, Jinge Wang +1

Video super-resolution, which attempts to reconstruct high-resolution video frames from their corresponding low-resolution versions, has received increasingly more attention in rec…

cs.CV2020

Accurate and Lightweight Image Super-Resolution with Model-Guided Deep Unfolding Network

Qian Ning, Weisheng Dong, Guangming Shi +2

Deep neural networks (DNNs) based methods have achieved great success in single image super-resolution (SISR). However, existing state-of-the-art SISR techniques are designed like…

eess.IV2018

Learning Hybrid Sparsity Prior for Image Restoration: Where Deep Learning Meets Sparse Coding

Fangfang Wu, Weisheng Dong, Guangming Shi +1

State-of-the-art approaches toward image restoration can be classified into model-based and learning-based. The former - best represented by sparse coding techniques - strive to ex…

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