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Chuanbiao Song

7 papers hereh-index 61k citations9 works total

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

author position
  • first author2
  • middle author5

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

fields
  • cs.CV4
  • cs.LG3
same name
  • Chuanbiao Song — 8 papers, h 4
  • Chuanbiao Song — 1 paper, 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

activity
20182026
most citedNesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks

230 citations · 342 across the 7 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild

Aleksandr Gushchin, Khaled Abud, Ekaterina Shumitskaya +51

This paper presents an overview of the NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild, held in conjunction with the NTIRE workshop at CVPR 2026. The goal o…

cs.CV2021★ 1 cited

Adversarial Attacks on ML Defense Models Competition

Yinpeng Dong, Qi-An Fu, Xiao Yang +25

Due to the vulnerability of deep neural networks (DNNs) to adversarial examples, a large number of defense techniques have been proposed to alleviate this problem in recent years.…

cs.CV2021★ 5 cited

Regional Adversarial Training for Better Robust Generalization

Chuanbiao Song, Yanbo Fan, Yichen Yang +4

Adversarial training (AT) has been demonstrated as one of the most promising defense methods against various adversarial attacks. To our knowledge, existing AT-based methods usuall…

cs.CV2019★ 20 cited

AT-GAN: An Adversarial Generator Model for Non-constrained Adversarial Examples

Xiaosen Wang, Kun He, Chuanbiao Song +2

Despite the rapid development of adversarial machine learning, most adversarial attack and defense researches mainly focus on the perturbation-based adversarial examples, which is…

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