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Jindong Gu
Jindong Gu
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
762018
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
262020
Saliency methods for explaining adversarial attacks
J Gu, V Tresp
Workshop on Human-Centric Machine Learning, NeurIPS 2019, 2019
212019
Search for better students to learn distilled knowledge
J Gu, V Tresp
European Conference on Artificial Intelligence (ECAI), 1159-1165, 2020
172020
Interpretable graph capsule networks for object recognition
J Gu
Proceedings of the AAAI Conference on Artificial Intelligence 35 (2), 1469-1477, 2021
132021
Understanding bias in machine learning
J Gu, D Oelke
Workshop on Visualization for AI Explainability, IEEE Vis 2018, 2019
122019
Semantics for global and local interpretation of deep neural networks
J Gu, V Tresp
International Joint Conference on Neural Networks, 1-8, 2019
112019
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
102021
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
92021
Are Vision Transformers Robust to Patch Perturbations?
J Gu, V Tresp, Y Qin
European Conference on Computer Vision (ECCV), 404-421, 2021
82021
Effective and Efficient Vote Attack on Capsule Networks
J Gu, B Wu, V Tresp
International Conference on Learning Representations (ICLR), 2021, 2021
82021
Contextual prediction difference analysis for explaining individual image classifications
J Gu, V Tresp
arXiv preprint arXiv:1910.09086, 2019
8*2019
Simple Distillation Baselines for Improving Small Self-supervised Models
J Gu, W Liu, Y Tian
Workshop on SSL for Autonomous Driving, ICCV 2021, 2021
32021
Adversarial Examples on Segmentation Models Can be Easy to Transfer
J Gu, H Zhao, V Tresp, P Torr
arXiv preprint arXiv:2111.11368, 2021
22021
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
12022
CL-CrossVQA: A Continual Learning Benchmark for Cross-Domain Visual Question Answering
Y Zhang, H Chen, A Frikha, Y Yang, D Krompass, G Zhang, J Gu, V Tresp
arXiv preprint arXiv:2211.10567, 2022
2022
Explainability and robustness of deep visual classification models
J Gu
University of Munich, 2022
2022
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
2022
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
2022
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