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Xiang Li

4 papers hereh-index 101.3k citations16 works total

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

author position
  • first author2
  • middle author2

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

fields
  • cs.CV4
same name
  • Xiang Li — 39 papers
  • Xiang Li — 26 papers, h 32
  • Xiang Li — 22 papers, h 21
  • Xiang Li — 13 papers, h 17
  • Xiang Li — 12 papers
  • Xiang Li — 10 papers, h 4

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
20162019
most citedCross-view Relation Networks for Mammogram Mass Detection

16 citations · 16 across the 1 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2019★ 16 cited

Cross-view Relation Networks for Mammogram Mass Detection

Jiechao Ma, Sen Liang, Xiang Li +4

Mammogram is the most effective imaging modality for the mass lesion detection of breast cancer at the early stage. The information from the two paired views (i.e., medio-lateral o…

cs.CV2019

Towards Photo-Realistic Visible Watermark Removal with Conditional Generative Adversarial Networks

Xiang Li, Chan Lu, Danni Cheng +5

Visible watermark plays an important role in image copyright protection and the robustness of a visible watermark to an attack is shown to be essential. To evaluate and improve the…

cs.CV2018

Adversarial Open-World Person Re-Identification

Xiang Li, Ancong Wu, Wei-Shi Zheng

In a typical real-world application of re-id, a watch-list (gallery set) of a handful of target people (e.g. suspects) to track around a large volume of non-target people are deman…

cs.CV2016

Top-push Video-based Person Re-identification

Jinjie You, Ancong Wu, Xiang Li +1

Most existing person re-identification (re-id) models focus on matching still person images across disjoint camera views. Since only limited information can be exploited from still…

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