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Zhan Qin

16 papers hereh-index 385.7k citations77 works total

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

author position
  • middle author12
  • last author3

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CR10
  • cs.CV4
  • cs.LG1
  • cs.MM1
same name
  • Zhan Qin — 18 papers, h 9
  • Zhan Qin — 9 papers, h 6
  • Zhan Qin — 9 papers, h 3
  • Zhan Qin — 9 papers, h 2
  • Zhan Qin — 6 papers, h 5
  • Zhan Qin — 6 papers, h 4

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
20152023
most citedBackdoor Defense via Decoupling the Training Process

42 citations · 96 across the 16 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2023★ 1 cited

SurrogatePrompt: Bypassing the Safety Filter of Text-to-Image Models via Substitution

Zhongjie Ba, Jieming Zhong, Jiachen Lei +5

Advanced text-to-image models such as DALL⋅E 2 and Midjourney possess the capacity to generate highly realistic images, raising significant concerns regarding the potential p…

cs.CV2023

RemovalNet: DNN Fingerprint Removal Attacks

Hongwei Yao, Zheng Li, Kunzhe Huang +3

With the performance of deep neural networks (DNNs) remarkably improving, DNNs have been widely used in many areas. Consequently, the DNN model has become a valuable asset, and its…

cs.CV2022★ 2 cited

Vanilla Feature Distillation for Improving the Accuracy-Robustness Trade-Off in Adversarial Training

Guodong Cao, Zhibo Wang, Xiaowei Dong +4

Adversarial training has been widely explored for mitigating attacks against deep models. However, most existing works are still trapped in the dilemma between higher accuracy and…

cs.CV2021★ 3 cited

Feature Importance-aware Transferable Adversarial Attacks

Zhibo Wang, Hengchang Guo, Zhifei Zhang +3

Transferability of adversarial examples is of central importance for attacking an unknown model, which facilitates adversarial attacks in more practical scenarios, e.g., black-box…

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