关注
Zhishuai Zhang
Zhishuai Zhang
Member of Technical Staff
在 openai.com 的电子邮件经过验证
标题
引用次数
引用次数
年份
Mitigating adversarial effects through randomization
C Xie, J Wang, Z Zhang, Z Ren, A Yuille
International Conference on Learning Representations 2018, 2017
12032017
Improving transferability of adversarial examples with input diversity
C Xie, Z Zhang, Y Zhou, S Bai, J Wang, Z Ren, AL Yuille
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
11582019
Adversarial examples for semantic segmentation and object detection
C Xie, J Wang, Z Zhang, Y Zhou, L Xie, A Yuille
Proceedings of the IEEE international conference on computer vision, 1369-1378, 2017
10892017
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
9682023
Deep co-training for semi-supervised image recognition
S Qiao, W Shen, Z Zhang, B Wang, A Yuille
Proceedings of the european conference on computer vision (eccv), 135-152, 2018
5032018
Technical report on the cleverhans v2. 1.0 adversarial examples library
N Papernot, F Faghri, N Carlini, I Goodfellow, R Feinman, A Kurakin, ...
arXiv preprint arXiv:1610.00768, 2016
4152016
Adversarial attacks and defences competition
A Kurakin, I Goodfellow, S Bengio, Y Dong, F Liao, M Liang, T Pang, ...
The NIPS'17 Competition: Building Intelligent Systems, 195-231, 2018
3712018
Single-shot object detection with enriched semantics
Z Zhang, S Qiao, C Xie, W Shen, B Wang, AL Yuille
Proceedings of the IEEE conference on computer vision and pattern …, 2018
2502018
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
1732024
Learning transferable adversarial examples via ghost networks
Y Li, S Bai, Y Zhou, C Xie, Z Zhang, A Yuille
Proceedings of the AAAI conference on artificial intelligence 34 (07), 11458 …, 2020
1322020
Noise2music: Text-conditioned music generation with diffusion models
Q Huang, DS Park, T Wang, TI Denk, A Ly, N Chen, Z Zhang, Z Zhang, ...
arXiv preprint arXiv:2302.03917, 2023
1122023
Combining compositional models and deep networks for robust object classification under occlusion
A Kortylewski, Q Liu, H Wang, Z Zhang, A Yuille
Proceedings of the IEEE/CVF winter conference on applications of computer …, 2020
732020
Stinet: Spatio-temporal-interactive network for pedestrian detection and trajectory prediction
Z Zhang, J Gao, J Mao, Y Liu, D Anguelov, C Li
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
712020
Deepvoting: A robust and explainable deep network for semantic part detection under partial occlusion
Z Zhang, C Xie, J Wang, L Xie, AL Yuille
Proceedings of the IEEE conference on computer vision and pattern …, 2018
61*2018
Unsupervised learning of object semantic parts from internal states of cnns by population encoding
J Wang, Z Zhang, C Xie, V Premachandran, A Yuille
arXiv preprint arXiv:1511.06855, 2015
61*2015
Hyper-pairing network for multi-phase pancreatic ductal adenocarcinoma segmentation
Y Zhou, Y Li, Z Zhang, Y Wang, A Wang, EK Fishman, AL Yuille, S Park
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
602019
Robust face detection via learning small faces on hard images
Z Zhang, W Shen, S Qiao, Y Wang, B Wang, A Yuille
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2020
562020
Visual concepts and compositional voting
J Wang, Z Zhang, C Xie, Y Zhou, V Premachandran, J Zhu, L Xie, A Yuille
Annals of Mathematical Sciences and Applications, 2017
522017
Detecting semantic parts on partially occluded objects
J Wang, C Xie, Z Zhang, J Zhu, L Xie, A Yuille
British Machine Vision Conference 2017, 2017
442017
Learning part segmentation through unsupervised domain adaptation from synthetic vehicles
Q Liu, A Kortylewski, Z Zhang, Z Li, M Guo, Q Liu, X Yuan, J Mu, W Qiu, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
24*2022
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