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Xiaoqiang Li

4 papers hereh-index 16698 citations57 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.CV3
  • cs.MM1
same name
  • Xiaoqiang Li — 4 papers, h 3
  • Xiaoqiang Li — 3 papers, h 4
  • Xiaoqiang Li — 3 papers, h 2
  • Xiaoqiang Li — 3 papers, h 19
  • Xiaoqiang Li — 2 papers, h 2
  • Xiaoqiang Li — 2 papers, h 3

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 citedStegNet: Mega Image Steganography Capacity with Deep Convolutional Network

151 citations · 154 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2021★ 1 cited

Reasoning Structural Relation for Occlusion-Robust Facial Landmark Localization

Congcong Zhu, Xiaoqiang Li, Jide Li +2

In facial landmark localization tasks, various occlusions heavily degrade the localization accuracy due to the partial observability of facial features. This paper proposes a struc…

cs.CV2021

Unsupervised Learning of Multi-level Structures for Anomaly Detection

Songmin Dai, Jide Li, Lu Wang +3

The main difficulty in high-dimensional anomaly detection tasks is the lack of anomalous data for training. And simply collecting anomalous data from the real world, common distrib…

cs.CV2018★ 2 cited

Learning Segmentation Masks with the Independence Prior

Songmin Dai, Xiaoqiang Li, Lu Wang +3

An instance with a bad mask might make a composite image that uses it look fake. This encourages us to learn segmentation by generating realistic composite images. To achieve this,…

cs.MM2018★ 151 cited

StegNet: Mega Image Steganography Capacity with Deep Convolutional Network

Pin Wu, Yang Yang, Xiaoqiang Li

Traditional image steganography often leans interests towards safely embedding hidden information into cover images with payload capacity almost neglected. This paper combines rece…

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