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Linlin Shen

14 papers hereh-index 6104 citations19 works total

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

author position
  • middle author8
  • last author5

Across the 13 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CV14
same name
  • Linlin Shen — 52 papers, h 37
  • Linlin Shen — 20 papers, h 10
  • Linlin Shen — 18 papers, h 13
  • LinLin Shen — 15 papers, h 6
  • Linlin Shen — 8 papers, h 7
  • Linlin Shen — 7 papers, h 5

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
20242026
most citedGM-DF: Generalized Multi-Scenario Deepfake Detection

6 citations · 7 across the 13 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CV2024

SFDA-rPPG: Source-Free Domain Adaptive Remote Physiological Measurement with Spatio-Temporal Consistency

Yiping Xie, Zitong Yu, Bingjie Wu +2

Remote Photoplethysmography (rPPG) is a non-contact method that uses facial video to predict changes in blood volume, enabling physiological metrics measurement. Traditional rPPG m…

cs.CV2024★ 1 cited

MFCLIP: Multi-modal Fine-grained CLIP for Generalizable Diffusion Face Forgery Detection

Yaning Zhang, Tianyi Wang, Zitong Yu +3

The rapid development of photo-realistic face generation methods has raised significant concerns in society and academia, highlighting the urgent need for robust and generalizable…

cs.CV2024★ 6 cited

GM-DF: Generalized Multi-Scenario Deepfake Detection

Yingxin Lai, Zitong Yu, Jing Yang +3

Existing face forgery detection usually follows the paradigm of training models in a single domain, which leads to limited generalization capacity when unseen scenarios and unknown…

cs.CV2024

GenFace: A Large-Scale Fine-Grained Face Forgery Benchmark and Cross Appearance-Edge Learning

Yaning Zhang, Zitong Yu, Tianyi Wang +4

The rapid advancement of photorealistic generators has reached a critical juncture where the discrepancy between authentic and manipulated images is increasingly indistinguishable.…

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