| Learning from simulated and unsupervised images through adversarial training A Shrivastava, T Pfister, O Tuzel, J Susskind, W Wang, R Webb Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1483 | 2017 |
| Flowing convnets for human pose estimation in videos T Pfister, J Charles, A Zisserman Proceedings of the IEEE international conference on computer vision, 1913-1921, 2015 | 494 | 2015 |
| Recognising Spontaneous Facial Micro-expressions T Pfister, X Li, G Zhao, M Pietikäinen International Conference on Computer Vision (ICCV), 2011 | 358 | 2011 |
| A Spontaneous Micro-expression Database: Inducement, Collection and Baseline X Li, T Pfister, X Huang, G Zhao, M Pietikäinen Automatic Face and Gesture Recognition (FG), 2013 | 328 | 2013 |
| Towards reading hidden emotions: A comparative study of spontaneous micro-expression spotting and recognition methods X Li, X Hong, A Moilanen, X Huang, T Pfister, G Zhao, M Pietikäinen IEEE transactions on affective computing 9 (4), 563-577, 2017 | 207 | 2017 |
| Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos T Pfister, K Simonyan, J Charles, A Zisserman Asian Conference on Computer Vision (ACCV), 2014 | 149 | 2014 |
| Differentiating Spontaneous From Posed Facial Expressions Within a Generic Facial Expression Recognition Framework T Pfister, X Li, G Zhao, M Pietikäinen International Conference on Computer Vision (ICCV) Workshops, 2011 | 99 | 2011 |
| Personalizing human video pose estimation J Charles, T Pfister, D Magee, D Hogg, A Zisserman Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 84 | 2016 |
| Tabnet: Attentive interpretable tabular learning SO Arık, T Pfister arXiv, 2020 | 71 | 2020 |
| Automatic and Efficient Human Pose Estimation for Sign Language Videos J Charles, T Pfister, M Everingham, A Zisserman International Journal of Computer Vision, 1-21, 2013 | 68 | 2013 |
| Real-Time Recognition of Affective States from Nonverbal Features of Speech and Its Application for Public Speaking Skill Analysis T Pfister, P Robinson IEEE Transactions on Affective Computing 2 (2), 66-78, 2011 | 67 | 2011 |
| Domain-adaptive discriminative one-shot learning of gestures T Pfister, J Charles, A Zisserman European Conference on Computer Vision, 814-829, 2014 | 65 | 2014 |
| Temporal fusion transformers for interpretable multi-horizon time series forecasting B Lim, SÖ Arık, N Loeff, T Pfister International Journal of Forecasting, 2021 | 57 | 2021 |
| A Simple Semi-Supervised Learning Framework for Object Detection K Sohn, Z Zhang, CL Li, H Zhang, CY Lee, T Pfister arXiv preprint arXiv:2005.04757, 2020 | 49 | 2020 |
| Large-scale Learning of Sign Language by Watching TV (Using Co-occurrences). T Pfister, J Charles, A Zisserman BMVC, 2013 | 49 | 2013 |
| Reading hidden emotions: spontaneous micro-expression spotting and recognition X Li, X Hong, A Moilanen, X Huang, T Pfister, G Zhao, M Pietikäinen arXiv preprint arXiv:1511.00423 12, 32-33, 2015 | 48 | 2015 |
| On completeness-aware concept-based explanations in deep neural networks CK Yeh, B Kim, SO Arik, CL Li, T Pfister, P Ravikumar arXiv preprint arXiv:1910.07969, 2019 | 41* | 2019 |
| Distilling effective supervision from severe label noise Z Zhang, H Zhang, SO Arik, H Lee, T Pfister Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 39 | 2020 |
| Speech emotion classification and public speaking skill assessment T Pfister, P Robinson Human Behavior Understanding Workshop, International Conference on Pattern …, 2010 | 37 | 2010 |
| Domain adaptation for upper body pose tracking in signed TV broadcasts J Charles, T Pfister, D Magee, D Hogg, A Zisserman British Machine Vision Association, 2013 | 35 | 2013 |
Sercan O. ArikGoogleVerified email at google.com
