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Xiaobo Wang

10 papers hereh-index 141.2k citations23 works total

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

author position
  • first author2
  • middle author7
  • last author1

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • eess.AS1
same name
  • Xiaobo Wang — 7 papers, h 35
  • Xiaobo Wang — 7 papers, h 4
  • Xiaobo Wang — 3 papers, h 0
  • Xiaobo Wang — 2 papers, h 3
  • Xiaobo Wang — 2 papers, h 7
  • Xiaobo Wang — 2 papers, h 2

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 citedLoss Function Search for Face Recognition

29 citations · 122 across the 10 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019★ 13 cited

Mis-classified Vector Guided Softmax Loss for Face Recognition

Xiaobo Wang, Shifeng Zhang, Shuo Wang +3

Face recognition has witnessed significant progress due to the advances of deep convolutional neural networks (CNNs), the central task of which is how to improve the feature discri…

cs.CV2019★ 10 cited

A High-Efficiency Framework for Constructing Large-Scale Face Parsing Benchmark

Yinglu Liu, Hailin Shi, Yue Si +3

Face parsing, which is to assign a semantic label to each pixel in face images, has recently attracted increasing interest due to its huge application potentials. Although many fac…

cs.CV2019★ 5 cited

Grand Challenge of 106-Point Facial Landmark Localization

Yinglu Liu, Hao Shen, Yue Si +18

Facial landmark localization is a very crucial step in numerous face related applications, such as face recognition, facial pose estimation, face image synthesis, etc. However, pre…

cs.CV2019★ 10 cited

Prediction-Tracking-Segmentation

Jianren Wang, Yihui He, Xiaobo Wang +2

We introduce a prediction driven method for visual tracking and segmentation in videos. Instead of solely relying on matching with appearance cues for tracking, we build a predicti…

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