Author

Chengzhi Mao

Observed name: Mao, Chengzhi

Institutions: Rutgers, The State University of New Jersey, Rutgers Sexual and Reproductive Health and Rights

Observed institutions: Rutgers, The State University of New Jersey, Rutgers Sexual and Reproductive Health and Rights, McGill University, Columbia University, Tsinghua University

ORCID: 0009-0003-2649-3368

Observed ORCID: 0009-0003-2649-3368

OpenAlex ID: A5061451821

Metric Learning for Adversarial Robustness

2019 · Mao, Chengzhi, Zhong, Ziyuan, et al. · arXiv (Cornell University) · 149

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Multitask Learning Strengthens Adversarial Robustness

2020 · Chengzhi Mao, Amogh Gupta, et al. · Lecture notes in computer science · 60

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Generative Interventions for Causal Learning

2021 · Chengzhi Mao, Augustine Cha, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 52

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Adversarial Attacks are Reversible with Natural Supervision

2021 · Chengzhi Mao, Mia Chiquier, et al. · IEEE/CVF International Conference on Computer Vision (ICCV) · 36

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A Probabilistic Learning Approach to UWB Ranging Error Mitigation

2018 · Chengzhi Mao, Kangbo Lin, et al. · Globecom · 32

Live Trojan Attacks on Deep Neural Networks

2020 · Robby Costales, Chengzhi Mao, et al. · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · 30

Causal Transportability for Visual Recognition

2022 · Chengzhi Mao, Kevin Xia, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 28

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Doubly Right Object Recognition: A Why Prompt for Visual Rationales

2023 · Chengzhi Mao, Revant Teotia, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 26

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Understanding Zero-Shot Adversarial Robustness for Large-Scale Models

2022 · Mao, Chengzhi, Geng, Scott, et al. · arXiv (Cornell University) · 19

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Discrete Representations Strengthen Vision Transformer Robustness

2021 · Mao, Chengzhi, Jiang, Lu, et al. · arXiv (Cornell University) · 16

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ImageNet-D: Benchmarking Neural Network Robustness on Diffusion Synthetic Object

2024 · Chenshuang Zhang, Fei Pan, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 15

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Raidar: geneRative AI Detection viA Rewriting

2024 · Mao, Chengzhi, Vondrick, Carl, et al. · arXiv (Cornell University) · 13

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Bidirectional Inference Networks:A Class of Deep Bayesian Networks for Health Profiling

2019 · Hao Wang, Chengzhi Mao, et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 13

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AdvSPADE: Realistic Unrestricted Attacks for Semantic Segmentation

2019 · Shen, Guangyu, Mao, Chengzhi, et al. · arXiv (Cornell University) · 11

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What You Can Reconstruct from a Shadow

2023 · Ruoshi Liu, Sachit Menon, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 6

Landscape Learning for Neural Network Inversion

2023 · Ruoshi Liu, Chengzhi Mao, et al. · IEEE/CVF International Conference on Computer Vision (ICCV) · 5

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Shadows Shed Light on 3D Objects

2022 · Liu, Ruoshi, Menon, Sachit, et al. · arXiv (Cornell University) · 5

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Real-Time Neural Voice Camouflage

2021 · Chiquier, Mia, Mao, Chengzhi, et al. · arXiv (Cornell University) · 5

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I Can Hear You: Selective Robust Training for Deepfake Audio Detection

2024 · Zhang, Zirui, Hao, Wei, et al. · arXiv (Cornell University) · 4

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