Follow
Jindong Gu
Jindong Gu
University of Oxford & Google DeepMind
Verified email at robots.ox.ac.uk - Homepage
Title
Cited by
Cited by
Year
Understanding individual decisions of cnns via contrastive backpropagation
J Gu, Y Yang, V Tresp
Proceedings of the Asian Conference on Computer Vision (ACCV), 119-134, 2018
1162018
Improving the robustness of capsule networks to image affine transformations
J Gu, V Tresp
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 7285-7293, 2020
552020
A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models
J Gu, Z Han, S Chen, A Beirami, B He, G Zhang, R Liao, Y Qin, V Tresp, ...
arXiv preprint arXiv:2307.12980, 2023
542023
Are vision transformers robust to patch perturbations?
J Gu, V Tresp, Y Qin
European Conference on Computer Vision (ECCV), 404-421, 2022
512022
Segpgd: An effective and efficient adversarial attack for evaluating and boosting segmentation robustness
J Gu, H Zhao, V Tresp, PHS Torr
European Conference on Computer Vision (ECCV), 308-325, 2022
512022
Fraug: Tackling federated learning with non-iid features via representation augmentation
H Chen, A Frikha, D Krompass, J Gu, V Tresp
International Conference on Computer Vision (ICCV), 2023, 4849-4859, 2023
492023
Towards efficient adversarial training on vision transformers
B Wu*, J Gu*, Z Li, D Cai, X He, W Liu
European Conference on Computer Vision (ECCV), 307-325, 2022
342022
Interpretable graph capsule networks for object recognition
J Gu
Proceedings of the AAAI Conference on Artificial Intelligence 35 (2), 1469-1477, 2021
312021
Capsule network is not more robust than convolutional network
J Gu, V Tresp, H Hu
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 14309-14317, 2021
312021
Saliency methods for explaining adversarial attacks
J Gu, V Tresp
Workshop on Human-Centric Machine Learning, NeurIPS 2019, 2019
312019
Effective and Efficient Vote Attack on Capsule Networks
J Gu, B Wu, V Tresp
International Conference on Learning Representations (ICLR), 2021, 2021
302021
Attacking Adversarial Attacks as A Defense
B Wu, H Pan, L Shen, J Gu, S Zhao, Z Li, D Cai, X He, W Liu
arXiv preprint arXiv:2106.04938, 2021
292021
Understanding bias in machine learning
J Gu, D Oelke
Workshop on Visualization for AI Explainability, IEEE Vis 2018, 2019
292019
Backdoor Defense via Adaptively Splitting Poisoned Dataset
K Gao, Y Bai, J Gu, Y Yang, ST Xia
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 4005-4014, 2023
272023
Search for better students to learn distilled knowledge
J Gu, V Tresp
European Conference on Artificial Intelligence (ECAI), 1159-1165, 2020
222020
Watermark vaccine: Adversarial attacks to prevent watermark removal
X Liu, J Liu, Y Bai, J Gu, T Chen, X Jia, X Cao
European Conference on Computer Vision (ECCV), 1-17, 2022
212022
Semantics for global and local interpretation of deep neural networks
J Gu, V Tresp
arXiv preprint arXiv:1910.09085, 2019
152019
Adversarial examples on segmentation models can be easy to transfer
J Gu, H Zhao, V Tresp, P Torr
arXiv preprint arXiv:2111.11368, 2021
132021
Contextual prediction difference analysis for explaining individual image classifications
J Gu, V Tresp
arXiv preprint arXiv:1910.09086, 2019
122019
ECOLA: Enhanced Temporal Knowledge Embeddings with Contextualized Language Representations
Z Han, R Liao, J Gu, Y Zhang, Z Ding, Y Gu, H Köppl, H Schütze, V Tresp
Findings of the Association for Computational Linguistics: ACL 2023, 2022
11*2022
The system can't perform the operation now. Try again later.
Articles 1–20