Zhiqiang Tang
Zhiqiang Tang
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Jointly optimize data augmentation and network training: Adversarial data augmentation in human pose estimation
X Peng*, Z Tang*, F Yang, RS Feris, D Metaxas
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
Quantized densely connected u-nets for efficient landmark localization
Z Tang, X Peng, S Geng, L Wu, S Zhang, D Metaxas
Proceedings of the European conference on computer vision (ECCV), 339-354, 2018
Semantic-guided multi-attention localization for zero-shot learning
Y Zhu, J Xie, Z Tang, X Peng, A Elgammal
Advances in Neural Information Processing Systems 32, 2019
Towards efficient u-nets: A coupled and quantized approach
Z Tang, X Peng, K Li, DN Metaxas
IEEE transactions on pattern analysis and machine intelligence 42 (8), 2038-2050, 2019
OnlineAugment: Online data augmentation with less domain knowledge
Z Tang, Y Gao, L Karlinsky, P Sattigeri, R Feris, D Metaxas
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Crossnorm and selfnorm for generalization under distribution shifts
Z Tang, Y Gao, Y Zhu, Z Zhang, M Li, DN Metaxas
Proceedings of the IEEE/CVF International Conference on Computer Vision, 52-61, 2021
CU-Net: Coupled U-Nets
Z Tang, X Peng, S Geng, Y Zhu, D Metaxas
BMVC 2018, 2018
Visual prompt tuning for test-time domain adaptation
Y Gao, X Shi, Y Zhu, H Wang, Z Tang, X Zhou, M Li, DN Metaxas
arXiv preprint arXiv:2210.04831, 2022
Toward marker-free 3D pose estimation in lifting: A deep multi-view solution
R Mehrizi, X Peng, Z Tang, X Xu, D Metaxas, K Li
2018 13th IEEE international conference on automatic face & gesture …, 2018
Enabling data diversity: efficient automatic augmentation via regularized adversarial training
Y Gao, Z Tang, M Zhou, D Metaxas
International Conference on Information Processing in Medical Imaging, 85-97, 2021
Are Multimodal Models Robust to Image and Text Perturbations?
J Qiu, Y Zhu, X Shi, F Wenzel, Z Tang, D Zhao, B Li, M Li
arXiv preprint arXiv:2212.08044, 2022
Adatransform: Adaptive data transformation
Z Tang, X Peng, T Li, Y Zhu, DN Metaxas
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Learning Multimodal Data Augmentation in Feature Space
Z Liu, Z Tang, X Shi, A Zhang, M Li, A Shrivastava, AG Wilson
The International Conference on Learning Representations (ICLR), 2023
The importance of 3D motion trajectories for computer-based sign recognition
M Dilsizian, Z Tang, D Metaxas, M Huenerfauth, C Neidle
sign-lang@ LREC 2016, 53-58, 2016
Face clustering in videos with proportion prior
Z Tang, Y Zhang, Z Li, H Lu
Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
A coupled hidden conditional random field model for simultaneous face clustering and naming in videos
Y Zhang, Z Tang, B Wu, Q Ji, H Lu
IEEE Transactions on Image Processing 25 (12), 5780-5792, 2016
Automatic face annotation in TV series by video/script alignment
Y Zhang, Z Tang, C Zhang, J Liu, H Lu
Neurocomputing 152, 316-321, 2015
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
Z Zhong, Z Tang, T He, H Fang, C Yuan
The International Conference on Learning Representations (ICLR), 2024
Benchmarking robustness under distribution shift of multimodal image-text models
J Qiu, Y Zhu, X Shi, Z Tang, D Zhao, B Li, M Li
NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022
Video face naming using global sequence alignment
Z Tang, Y Zhang, S Qiu, H Lu
2014 IEEE International Conference on Image Processing (ICIP), 353-357, 2014
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