| A generative adversarial approach for zero-shot learning from noisy texts Y Zhu, M Elhoseiny, B Liu, X Peng, A Elgammal Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 406 | 2018 |
| Semantic Graph Convolutional Networks for 3D Human Pose Regression L Zhao, X Peng, Y Tian, M Kapadia, DN Metaxas IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 403 | 2019 |
| Learning to Learn Single Domain Generalization F Qiao, L Zhao, X Peng IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 12556-12565, 2020 | 258 | 2020 |
| Jointly optimize data augmentation and network training: Adversarial data augmentation X Peng, Z Tang, F Yang, RS Feris, D Metaxas Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 217* | 2018 |
| A recurrent encoder-decoder for sequential face alignment X Peng, RS Feris, X Wang, DN Metaxs European Conference on Computer Vision (Best Student Paper Runner-up), 38-56, 2016 | 173* | 2016 |
| Reconstruction-based disentanglement for pose-invariant face recognition X Peng, X Yu, K Sohn, DN Metaxas, M Chandraker Proceedings of the IEEE International Conference on Computer Vision (ICCV …, 2017 | 168 | 2017 |
| 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 | 148 | 2018 |
| CR-GAN: learning complete representations for multi-view generation Y Tian, X Peng, L Zhao, S Zhang, DN Metaxas International Joint Conference on Artificial Intelligence (IJCAI), 2018 | 142 | 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 (NeurIPS), 14943-14953, 2019 | 107 | 2019 |
| Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness L Zhao, T Liu, X Peng, D Metaxas Conference on Neural Information Processing Systems (NeurIPS), 2020 | 91 | 2020 |
| Learning to forecast and refine residual motion for image-to-video generation L Zhao, X Peng, Y Tian, M Kapadia, D Metaxas Proceedings of the European conference on computer vision (ECCV), 387-403, 2018 | 88 | 2018 |
| A good image generator is what you need for high-resolution video synthesis Y Tian, J Ren, M Chai, K Olszewski, X Peng, DN Metaxas, S Tulyakov The International Conference on Learning Representations (ICLR Spotlight), 2021 | 74 | 2021 |
| SMIL: Multimodal Learning with Severely Missing Modality M Ma, J Ren, L Zhao, S Tulyakov, C Wu, X Peng Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021 | 74 | 2021 |
| Construct dynamic graphs for hand gesture recognition via spatial-temporal attention Y Chen, L Zhao, X Peng, J Yuan, DN Metaxas British Machine Vision Conference (BMVC), 2019 | 67 | 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 (TPAMI), 2019 | 60 | 2019 |
| Piefa: Personalized incremental and ensemble face alignment X Peng, S Zhang, Y Yang, DN Metaxas Proceedings of the IEEE international conference on computer vision (ICCV …, 2015 | 56 | 2015 |
| A computer vision based method for 3D posture estimation of symmetrical lifting R Mehrizi, X Peng, X Xu, S Zhang, D Metaxas, K Li Journal of biomechanics (JoB) 69, 40-46, 2018 | 53 | 2018 |
| Knowledge as Priors: Cross-Modal Knowledge Generalization for Datasets without Superior Knowledge L Zhao, X Peng, Y Chen, M Kapadia, DN Metaxas IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 6528-6537, 2020 | 50 | 2020 |
| CU-net: coupled U-nets Z Tang, X Peng, S Geng, Y Zhu, DN Metaxas British Machine Vision Conference (BMVC Oral), 2018 | 49 | 2018 |
| 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 | 38 | 2018 |
Dimitris N. MetaxasDistinguished Professor of Computer Science, Rutgers UniversityEmail confirmado em cs.rutgers.edu
