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Shang-Hong Lai

National Tsing Hua University

15 papers hereh-index 345.5k citations318 works total

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

author position
  • middle author4
  • last author11

Across the 15 of 15 papers where every author was matched, so the position is known.

fields
  • cs.CV13
  • cs.MM1
  • eess.IV1
affiliations
  • National Tsing Hua University
  • Microsoft Inc
Homepage
same name
  • Shang-Hong Lai — 6 papers, h 3
  • Shang-Hong Lai — 3 papers, h 1
  • Shang-Hong Lai — 2 papers, h 4
  • Shang-Hong Lai — 1 paper, 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
20202023
most citedPatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition

10 citations · 25 across the 15 of their papers we have counts for

collaborators
Showing 2021Show all

3 papers · 1 filter

cs.CV2021

High-Accuracy RGB-D Face Recognition via Segmentation-Aware Face Depth Estimation and Mask-Guided Attention Network

Meng-Tzu Chiu, Hsun-Ying Cheng, Chien-Yi Wang +1

Deep learning approaches have achieved highly accurate face recognition by training the models with very large face image datasets. Unlike the availability of large 2D face image d…

cs.CV2021★ 1 cited

FedFR: Joint Optimization Federated Framework for Generic and Personalized Face Recognition

Chih-Ting Liu, Chien-Yi Wang, Shao-Yi Chien +1

Current state-of-the-art deep learning based face recognition (FR) models require a large number of face identities for central training. However, due to the growing privacy awaren…

cs.CV2021★ 2 cited

Disentangled Representation with Dual-stage Feature Learning for Face Anti-spoofing

Yu-Chun Wang, Chien-Yi Wang, Shang-Hong Lai

As face recognition is widely used in diverse security-critical applications, the study of face anti-spoofing (FAS) has attracted more and more attention. Several FAS methods have…

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