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Multimodal contrastive learning (MCL) has shown remarkable advances in zero-shot classification by learning from millions of image-caption pairs crawled from the Internet.
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Representation learning with contrastive predictive coding
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Poison frogs! targeted clean-label poisoning attacks on neural networks
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Transferable adversarial attacks for image and video object detection
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Badnets: Evaluating backdooring attacks on deep neural networks
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Towards unsupervised image captioning with shared multimodal embeddings. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 7414–7424
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TensorClog: An imperceptible poisoning attack on deep neural network applications
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Context-aware attention network for image-text retrieval. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 3536–3545
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Poisoning and backdooring contrastive learning
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Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 3558–3568
Soravit Changpinyo, Piyush Sharma, Nan Ding, and Radu Soricut. 2021 · 2021
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Privacy-enhancing face obfuscation guided by semantic-aware attribution maps
Privacy enhancing face obfuscation guided by semantic-aware attribution maps. 2023 · 2023
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Re-thinking Data Availablity Attacks Against Deep Neural Networks
Bin Fang, Bo Li, Shuang Wu, Ran Yi, Shouhong Ding, and Lizhuang Ma. 2023 · 2023
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Backdoor defense via adaptively splitting poisoned dataset. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 4005–4014
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A survey on transferability of adversarial examples across deep neural networks
Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqain Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, et al · 2023
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Adversarial examples make strong poisons
Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojciech Czaja, and Tom Goldstein. 2021 · 2021
Cited alongside, same era.
Effective and Efficient Vote Attack on Capsule Networks. In International Conference on Learning Representations (ICLR)
Jindong Gu, Baoyuan Wu, and Volker Tresp. 2021 · 2021
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Unlearnable examples: Making personal data unexploitable
Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani, James Bailey, and Yisen Wang. 2021b · 2021
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Scaling up visual and vision-language representation learning with noisy text supervision. In International conference on machine learning . PMLR, 4904–4916
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig. 2021 · 2021
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Generate more imperceptible adversarial examples for object detection. In ICML 2021 Workshop on Adversarial Machine Learning
Siyuan Liang, Xingxing Wei, and Xiaochun Cao. 2021 · 2021
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Poisoning attack against estimating from pairwise comparisons
Ke Ma, Qianqian Xu, Jinshan Zeng, Xiaochun Cao, and Qingming Huang. 2021 · 2021
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Clipcap: Clip prefix for image captioning
Ron Mokady, Amir Hertz, and Amit H Bermano. 2021 · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision. In International conference on machine learning . PMLR, 8748–8763
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Cited alongside, same era.
Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks. In Proceedings of the 31st ACM International Conference on Multimedia
Jun Guo, Xingyu Zheng, Aishan Liu, Siyuan Liang, Yisong Xiao, Yichao Wu, and Xianglong Liu. 2023 · 2023
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Badclip: Dual-embedding guided backdoor attack on multimodal contrastive learning
Siyuan Liang, Mingli Zhu, Aishan Liu, Baoyuan Wu, Xiaochun Cao, and Ee-Chien Chang. 2023 · 2023
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Pre-trained trojan attacks for visual recognition
Aishan Liu, Xinwei Zhang, Yisong Xiao, Yuguang Zhou, Siyuan Liang, Jiakai Wang, Xianglong Liu, Xiaochun Cao, and Dacheng Tao. 2023 · 2023
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Cuda: Convolution-based unlearnable datasets. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 3862–3871
Vinu Sankar Sadasivan, Mahdi Soltanolkotabi, and Soheil Feizi. 2023 · 2023
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Data poisoning attacks against multimodal encoders. In International Conference on Machine Learning . PMLR, 39299–39313
Ziqing Yang, Xinlei He, Zheng Li, Michael Backes, Mathias Humbert, Pascal Berrang, and Yang Zhang. 2023 · 2023
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Backdoor Attack with Sparse and Invisible Trigger
Yinghua Gao, Yiming Li, Xueluan Gong, Zhifeng Li, Shu-Tao Xia, and Qian Wang. 2024 · 2024
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Texture Re-scalable Universal Adversarial Perturbation
Yihao Huang, Qing Guo, Felix Juefei-Xu, Ming Hu, Xiaojun Jia, Xiaochun Cao, Geguang Pu, and Yang Liu. 2024a · 2024
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Revisiting and exploring efficient fast adversarial training via law: Lipschitz regularization and auto weight averaging
Xiaojun Jia, Yuefeng Chen, Xiaofeng Mao, Ranjie Duan, Jindong Gu, Rong Zhang, Hui Xue, Yang Liu, and Xiaochun Cao. 2024a · 2024
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Improving fast adversarial training with prior-guided knowledge
Xiaojun Jia, Yong Zhang, Xingxing Wei, Baoyuan Wu, Ke Ma, Jue Wang, and Xiaochun Cao. 2024b · 2024
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Influencer backdoor attack on semantic segmentation
Haoheng Lan, Jindong Gu, Philip Torr, and Hengshuang Zhao. 2024 · 2024
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Learning to Optimize Permutation Flow Shop Scheduling via Graph-based Imitation Learning
Longkang Li, Siyuan Liang, Zihao Zhu, Chris Ding, Hongyuan Zha, and Baoyuan Wu. 2024 · 2024
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Poisoned forgery face: Towards backdoor attacks on face forgery detection
Jiawei Liang, Siyuan Liang, Aishan Liu, Xiaojun Jia, Junhao Kuang, and Xiaochun Cao. 2024a · 2024
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VL-Trojan: Multimodal Instruction Backdoor Attacks against Autoregressive Visual Language Models
Jiawei Liang, Siyuan Liang, Man Luo, Aishan Liu, Dongchen Han, Ee-Chien Chang, and Xiaochun Cao. 2024b · 2024
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Siyuan Liang, Kuanrong Liu, Jiajun Gong, Jiawei Liang, Yuan Xun, Ee-Chien Chang, and Xiaochun Cao. 2024c · 2024
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Object Detectors in the Open Environment: Challenges, Solutions, and Outlook
Siyuan Liang, Wei Wang, Ruoyu Chen, Aishan Liu, Boxi Wu, Ee-Chien Chang, Xiaochun Cao, and Dacheng Tao. 2024d · 2024
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Does few-shot learning suffer from backdoor attacks?. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 38. 19893–19901
Xinwei Liu, Xiaojun Jia, Jindong Gu, Yuan Xun, Siyuan Liang, and Xiaochun Cao. 2024 · 2024
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Sequential manipulation against rank aggregation: theory and algorithm
Ke Ma, Qianqian Xu, Jinshan Zeng, Wei Liu, Xiaochun Cao, Yingfei Sun, and Qingming Huang. 2024 · 2024
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Minimalism is King! High-Frequency Energy-based Screening for Data-Efficient Backdoor Attacks
Yuan Xun, Xiaojun Jia, Jindong Gu, Xinwei Liu, Qing Guo, and Xiaochun Cao. 2024 · 2024
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Robust Contrastive Language-Image Pretraining against Data Poisoning and Backdoor Attacks
Wenhan Yang, Jingdong Gao, and Baharan Mirzasoleiman. 2024 · 2024
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Towards Robust Physical-world Backdoor Attacks on Lane Detection
Xinwei Zhang, Aishan Liu, Tianyuan Zhang, Siyuan Liang, and Xianglong Liu. 2024 · 2024
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Breaking the False Sense of Security in Backdoor Defense through Re-Activation Attack
Mingli Zhu, Siyuan Liang, and Baoyuan Wu. 2024 · 2024
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Styleclip: Text-driven manipulation of stylegan imagery. In Proceedings of the IEEE/CVF international conference on computer vision . 2085–2094
Or Patashnik, Zongze Wu, Eli Shechtman, Daniel Cohen-Or, and Dani Lischinski. 2021 · 2094
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