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Feng Lin

7 papers hereh-index 10369 citations26 works total

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

author position
  • middle author7

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.CR3
same name
  • Feng Lin — 7 papers, h 3
  • Feng Lin — 6 papers, h 2
  • Feng Lin — 5 papers, h 2
  • Feng Lin — 4 papers, h 17
  • Feng Lin — 4 papers, h 3
  • Feng Lin — 4 papers, h 1

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

most citedLocate and Verify: A Two-Stream Network for Improved Deepfake Detection

2 citations · 4 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2024

FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning

Gaojian Wang, Feng Lin, Tong Wu +3

This work asks: with abundant, unlabeled real faces, how to learn a robust and transferable facial representation that boosts various face security tasks with respect to generaliza…

cs.CV2024

Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection

Zhongjie Ba, Qingyu Liu, Zhenguang Liu +4

Deepfake technology has given rise to a spectrum of novel and compelling applications. Unfortunately, the widespread proliferation of high-fidelity fake videos has led to pervasive…

cs.CV2023★ 2 cited

Locate and Verify: A Two-Stream Network for Improved Deepfake Detection

Chao Shuai, Jieming Zhong, Shuang Wu +6

Deepfake has taken the world by storm, triggering a trust crisis. Current deepfake detection methods are typically inadequate in generalizability, with a tendency to overfit to ima…

cs.CV2023★ 1 cited

DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues

Kun Pan, Yin Yifang, Yao Wei +6

The malicious use and widespread dissemination of deepfake pose a significant crisis of trust. Current deepfake detection models can generally recognize forgery images by training…

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