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Xi Yin

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16 papers hereh-index 226.1k citations28 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.CV16
affiliations
  • Facebook
Homepage
same name
  • Xi Yin — 51 papers, h 40
  • Xi Yin — 14 papers, h 6
  • Xi Yin — 3 papers, h 4
  • Xi Yin — 3 papers, h 1
  • Xi Yin — 3 papers, h 3
  • Xi Yin — 2 papers, h 0

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
20152024
most citedMulti-Task Convolutional Neural Network for Pose-Invariant Face Recognition

256 citations · 610 across the 14 of their papers we have counts for

collaborators
Showing 2017Show all

4 papers · 1 filter

cs.CV2017★ 69 cited

Illuminating Pedestrians via Simultaneous Detection & Segmentation

Garrick Brazil, Xi Yin, Xiaoming Liu

Pedestrian detection is a critical problem in computer vision with significant impact on safety in urban autonomous driving. In this work, we explore how semantic segmentation can…

cs.CV2017★ 170 cited

Representation Learning by Rotating Your Faces

Luan Tran, Xi Yin, Xiaoming Liu

The large pose discrepancy between two face images is one of the fundamental challenges in automatic face recognition. Conventional approaches to pose-invariant face recognition ei…

cs.CV2017★ 42 cited

Towards Large-Pose Face Frontalization in the Wild

Xi Yin, Xiang Yu, Kihyuk Sohn +2

Despite recent advances in face recognition using deep learning, severe accuracy drops are observed for large pose variations in unconstrained environments. Learning pose-invariant…

cs.CV2017★ 256 cited

Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition

Xi Yin, Xiaoming Liu

This paper explores multi-task learning (MTL) for face recognition. We answer the questions of how and why MTL can improve the face recognition performance. First, we propose a mul…

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