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Junyi Zhu

12 papers hereh-index 11923 citations15 works total

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

author position
  • first author4
  • middle author4
  • last author3

Across the 11 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CV6
  • cs.LG6
same name
  • Junyi Zhu — 20 papers, h 21
  • Junyi Zhu — 7 papers, h 7
  • Junyi Zhu — 6 papers, h 3
  • Junyi Zhu — 3 papers, h 2
  • Junyi Zhu — 2 papers, h 1
  • Junyi Zhu — 2 papers, 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 citedRobustness and Accuracy Could Be Reconcilable by (Proper) Definition

26 citations · 87 across the 12 of their papers we have counts for

collaborators
Showing 2022 · cs.CVShow all

4 papers · 2 filters

cs.CV2022★ 17 cited

Isometric 3D Adversarial Examples in the Physical World

Yibo Miao, Yinpeng Dong, Jun Zhu +1

3D deep learning models are shown to be as vulnerable to adversarial examples as 2D models. However, existing attack methods are still far from stealthy and suffer from severe perf…

cs.CV2022★ 18 cited

ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints

Yinpeng Dong, Shouwei Ruan, Hang Su +3

Recent studies have demonstrated that visual recognition models lack robustness to distribution shift. However, current work mainly considers model robustness to 2D image transform…

cs.CV2022★ 1 cited

BadDet: Backdoor Attacks on Object Detection

Shih-Han Chan, Yinpeng Dong, Jun Zhu +2

Deep learning models have been deployed in numerous real-world applications such as autonomous driving and surveillance. However, these models are vulnerable in adversarial environ…

cs.CV2022★ 4 cited

Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognition

Xiao Yang, Yinpeng Dong, Tianyu Pang +3

Recent studies have revealed the vulnerability of face recognition models against physical adversarial patches, which raises security concerns about the deployed face recognition s…

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