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Tomas Pfister
Tomas Pfister
Head of AI Research @ Google Cloud
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
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
16622017
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
5492015
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
3962013
Recognising Spontaneous Facial Micro-expressions
T Pfister, X Li, G Zhao, M Pietikäinen
International Conference on Computer Vision (ICCV), 2011
3892011
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
2462017
Tabnet: Attentive interpretable tabular learning
SO Arık, T Pfister
AAAI 35, 6679-6687, 2021
1902021
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
1652014
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
1282020
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
1052011
Temporal fusion transformers for interpretable multi-horizon time series forecasting
B Lim, SO Arik, N Loeff, T Pfister
arXiv preprint arXiv:1912.09363, 2019
992019
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
912016
On completeness-aware concept-based explanations in deep neural networks
CK Yeh, B Kim, S Arik, CL Li, T Pfister, P Ravikumar
Advances in Neural Information Processing Systems 33, 20554-20565, 2020
84*2020
Cutpaste: Self-supervised learning for anomaly detection and localization
CL Li, K Sohn, J Yoon, T Pfister
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
792021
Temporal fusion transformers for interpretable multi-horizon time series forecasting
B Lim, SÖ Arık, N Loeff, T Pfister
International Journal of Forecasting 37 (4), 1748-1764, 2021
772021
Domain-adaptive discriminative one-shot learning of gestures
T Pfister, J Charles, A Zisserman
European Conference on Computer Vision, 814-829, 2014
772014
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
742013
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
672011
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
642020
Pseudoseg: Designing pseudo labels for semantic segmentation
Y Zou, Z Zhang, H Zhang, CL Li, X Bian, JB Huang, T Pfister
arXiv preprint arXiv:2010.09713, 2020
562020
Large-scale Learning of Sign Language by Watching TV (Using Co-occurrences).
T Pfister, J Charles, A Zisserman
BMVC, 2013
562013
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