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Xiaoming Li

16 papers hereh-index 182k citations34 works total

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

author position
  • first author4
  • middle author12

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CV15
  • eess.IV1
same name
  • Xiaoming Li — 9 papers, h 18
  • Xiaoming Li — 8 papers, h 11
  • Xiaoming Li — 8 papers, h 4
  • Xiaoming Li — 6 papers, h 4
  • Xiaoming Li — 5 papers, h 41
  • Xiaoming Li — 2 papers, h 7

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
20182025
most citedShift-Net: Image Inpainting via Deep Feature Rearrangement

46 citations · 108 across the 15 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.CV2018★ 2 cited

Learning Symmetry Consistent Deep CNNs for Face Completion

Xiaoming Li, Ming Liu, Jieru Zhu +4

Deep convolutional networks (CNNs) have achieved great success in face completion to generate plausible facial structures. These methods, however, are limited in maintaining global…

cs.CV2018★ 15 cited

Identity Preserving Face Completion for Large Ocular Region Occlusion

Yajie Zhao, Weikai Chen, Jun Xing +5

We present a novel deep learning approach to synthesize complete face images in the presence of large ocular region occlusions. This is motivated by recent surge of VR/AR displays…

cs.CV2018★ 9 cited

Learning Warped Guidance for Blind Face Restoration

Xiaoming Li, Ming Liu, Yuting Ye +3

This paper studies the problem of blind face restoration from an unconstrained blurry, noisy, low-resolution, or compressed image (i.e., degraded observation). For better recovery…

cs.CV2018★ 46 cited

Shift-Net: Image Inpainting via Deep Feature Rearrangement

Zhaoyi Yan, Xiaoming Li, Mu Li +2

Deep convolutional networks (CNNs) have exhibited their potential in image inpainting for producing plausible results. However, in most existing methods, e.g., context encoder, the…

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