When Measures are Unreliable: Imperceptible Adversarial Perturbations toward Top-k Multi-Label Learning

Author:

Sun Yuchen1ORCID,Xu Qianqian1ORCID,Wang Zitai2ORCID,Huang Qingming3ORCID

Affiliation:

1. IIP, ICT, CAS, Beijing, China

2. SKLOIS, IIE, CAS & SCS, UCAS, Beijing, China

3. SCST, UCAS; IIP, ICT, CAS; BDKM, CAS; & Peng Cheng Laboratory, Beijing, China

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

National Key R&D Program of China

Publisher

ACM

Reference64 articles.

1. Sandhya Aneja , Nagender Aneja , Pg Emeroylariffion Abas, and Abdul Ghani Naim . 2022 . Defense against adversarial attacks on deep convolutional neural networks through nonlocal denoising. CoRR , Vol. abs/ 2206 .12685 (2022). Sandhya Aneja, Nagender Aneja, Pg Emeroylariffion Abas, and Abdul Ghani Naim. 2022. Defense against adversarial attacks on deep convolutional neural networks through nonlocal denoising. CoRR, Vol. abs/2206.12685 (2022).

2. VIMES

3. Leonard Berrada , Andrew Zisserman , and M. Pawan Kumar . 2018 . Smooth Loss Functions for Deep Top-k Classification. In International Conference on Learning Representations. Leonard Berrada, Andrew Zisserman, and M. Pawan Kumar. 2018. Smooth Loss Functions for Deep Top-k Classification. In International Conference on Learning Representations.

4. Maurits J. R. Bleeker . 2022 . Multi-modal Learning Algorithms and Network Architectures for Information Extraction and Retrieval. In ACM International Conference on Multimedia. 6925--6929 . Maurits J. R. Bleeker. 2022. Multi-modal Learning Algorithms and Network Architectures for Information Extraction and Retrieval. In ACM International Conference on Multimedia. 6925--6929.

5. Nicholas Carlini and David A. Wagner . 2017 . Towards Evaluating the Robustness of Neural Networks. In IEEE Symposium on Security and Privacy. 39--57 . Nicholas Carlini and David A. Wagner. 2017. Towards Evaluating the Robustness of Neural Networks. In IEEE Symposium on Security and Privacy. 39--57.

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