Tomas Pfister

According to our database, Tomas Pfister authored at least 92 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding.

Zilong Wang, Hao Zhang, Chun-Liang Li, Julian Martin Eisenschlos, Vincent Perot, Zifeng Wang, Lesly Miculicich, Yasuhisa Fujii, Jingbo Shang, Chen-Yu Lee, Tomas Pfister

CoRR, 2024

2023

SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch.

Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister

Trans. Mach. Learn. Res., 2023

EHR-Safe: generating high-fidelity and privacy-preserving synthetic electronic health records.

Jinsung Yoon, Michel J. Mizrahi, Nahid Farhady Ghalaty, Thomas Jarvinen, Ashwin S. Ravi, Peter Brune, Fanyu Kong, Dave Anderson, George Lee, Arie Meir, Farhana Bandukwala, Elli Kanal, Sercan Ö. Arik, Tomas Pfister

npj Digit. Medicine, 2023

TextGenSHAP: Scalable Post-hoc Explanations in Text Generation with Long Documents.

James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister

CoRR, 2023

Effective Large Language Model Adaptation for Improved Grounding.

Xi Ye, Ruoxi Sun, Sercan Ö. Arik, Tomas Pfister

CoRR, 2023

COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning.

Chuizheng Meng, Yihe Dong, Sercan Ö. Arik, Yan Liu, Tomas Pfister

CoRR, 2023

Search-Adaptor: Text Embedding Customization for Information Retrieval.

Jinsung Yoon, Sercan Ö. Arik, Yanfei Chen, Tomas Pfister

CoRR, 2023

TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting.

Defu Cao, Furong Jia, Sercan Ö. Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu

CoRR, 2023

PAITS: Pretraining and Augmentation for Irregularly-Sampled Time Series.

Nicasia Beebe-Wang, Sayna Ebrahimi, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister

CoRR, 2023

Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models.

Cheng-Yu Hsieh, Si-An Chen, Chun-Liang Li, Yasuhisa Fujii, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister

CoRR, 2023

SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL.

Ruoxi Sun, Sercan Ö. Arik, Hootan Nakhost, Hanjun Dai, Rajarishi Sinha, Pengcheng Yin, Tomas Pfister

CoRR, 2023

LANISTR: Multimodal Learning from Structured and Unstructured Data.

Sayna Ebrahimi, Sercan Ö. Arik, Yihe Dong, Tomas Pfister

CoRR, 2023

ASPEST: Bridging the Gap Between Active Learning and Selective Prediction.

Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister

CoRR, 2023

TSMixer: An all-MLP Architecture for Time Series Forecasting.

Si-An Chen, Chun-Liang Li, Nate Yoder, Sercan Ö. Arik, Tomas Pfister

CoRR, 2023

Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types.

Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Unifying Distribution Alignment as a Loss for Imbalanced Semi-supervised Learning.

Justin Lazarow, Kihyuk Sohn, Chen-Yu Lee, Chun-Liang Li, Zizhao Zhang, Tomas Pfister

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Data-Efficient and Interpretable Tabular Anomaly Detection.

Chun-Hao Chang, Jinsung Yoon, Sercan Ö. Arik, Madeleine Udell, Tomas Pfister

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Universal Self-Adaptive Prompting.

Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Eisenschlos, Sercan Ö. Arik, Tomas Pfister

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data.

Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs.

Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval.

Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Prefix Conditioning Unifies Language and Label Supervision.

Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Better Zero-Shot Reasoning with Self-Adaptive Prompting.

Xingchen Wan, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arik, Tomas Pfister

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction.

Chen-Yu Lee, Chun-Liang Li, Hao Zhang, Timothy Dozat, Vincent Perot, Guolong Su, Xiang Zhang, Kihyuk Sohn, Nikolay Glushnev, Renshen Wang, Joshua Ainslie, Shangbang Long, Siyang Qin, Yasuhisa Fujii, Nan Hua, Tomas Pfister

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes.

Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

QueryForm: A Simple Zero-shot Form Entity Query Framework.

Zifeng Wang, Zizhao Zhang, Jacob Devlin, Chen-Yu Lee, Guolong Su, Hao Zhang, Jennifer G. Dy, Vincent Perot, Tomas Pfister

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Neural Spline Search for Quantile Probabilistic Modeling.

Ruoxi Sun, Chun-Liang Li, Sercan Ö. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection.

Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister

Trans. Mach. Learn. Res., 2022

LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling.

Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister

Trans. Mach. Learn. Res., 2022

Algorithmic fairness in pandemic forecasting: lessons from COVID-19.

Thomas C. Tsai, Sercan Ö. Arik, Benjamin H. Jacobson, Jinsung Yoon, Nate Yoder, Dario Sava, Margaret Mitchell, Garth Graham, Tomas Pfister

npj Digit. Medicine, 2022

Test-Time Adaptation for Visual Document Understanding.

Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister

CoRR, 2022

Invariant Structure Learning for Better Generalization and Causal Explainability.

Yunhao Ge, Sercan Ö. Arik, Jinsung Yoon, Ao Xu, Laurent Itti, Tomas Pfister

CoRR, 2022

Interpretable Mixture of Experts for Structured Data.

Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister

CoRR, 2022

Self-Adaptive Forecasting for Improved Deep Learning on Non-Stationary Time-Series.

Sercan Ö. Arik, Nathanael C. Yoder, Tomas Pfister

CoRR, 2022

Towards Group Robustness in the presence of Partial Group Labels.

Vishnu Suresh Lokhande, Kihyuk Sohn, Jinsung Yoon, Madeleine Udell, Chen-Yu Lee, Tomas Pfister

CoRR, 2022

Learning Instance-Specific Adaptation for Cross-Domain Segmentation.

Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang

Proceedings of the Computer Vision - ECCV 2022, 2022

DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning.

Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, Tomas Pfister

Proceedings of the Computer Vision - ECCV 2022, 2022

Learning to Prompt for Continual Learning.

Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, Tomas Pfister

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Decoupling Local and Global Representations of Time Series.

Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction.

Chen-Yu Lee, Chun-Liang Li, Timothy Dozat, Vincent Perot, Guolong Su, Nan Hua, Joshua Ainslie, Renshen Wang, Yasuhisa Fujii, Tomas Pfister

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Nested Hierarchical Transformer: Towards Accurate, Data-Efficient and Interpretable Visual Understanding.

Zizhao Zhang, Han Zhang, Long Zhao, Ting Chen, Sercan Ö. Arik, Tomas Pfister

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Learning from Weakly-Labeled Web Videos via Exploring Sub-concepts.

Kunpeng Li, Zizhao Zhang, Guanhang Wu, Xuehan Xiong, Chen-Yu Lee, Zhichao Lu, Yun Fu, Tomas Pfister

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan.

Sercan Ö. Arik, Joel Shor, Rajarishi Sinha, Jinsung Yoon, Joseph R. Ledsam, Long T. Le, Michael W. Dusenberry, Nathanael C. Yoder, Kris Popendorf, Arkady Epshteyn, Johan Euphrosine, Elli Kanal, Isaac Jones, Chun-Liang Li, Beth Luan, Joe Mckenna, Vikas Menon, Shashank Singh, Mimi Sun, Ashwin Sura Ravi, Leyou Zhang, Dario Sava, Kane Cunningham, Hiroki Kayama, Thomas C. Tsai, Daisuke Yoneoka, Shuhei Nomura, Hiroaki Miyata, Tomas Pfister

npj Digit. Medicine, 2021

Self-Trained One-class Classification for Unsupervised Anomaly Detection.

Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister

CoRR, 2021

Aggregating Nested Transformers.

Zizhao Zhang, Han Zhang, Long Zhao, Ting Chen, Tomas Pfister

CoRR, 2021

Controlling Neural Networks with Rule Representations.

Sungyong Seo, Sercan Ö. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PseudoSeg: Designing Pseudo Labels for Semantic Segmentation.

Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning and Evaluating Representations for Deep One-Class Classification.

Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Fast Sample Re-weighting Without Reward Data.

Zizhao Zhang, Tomas Pfister

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

CutPaste: Self-Supervised Learning for Anomaly Detection and Localization.

Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction.

Chen-Yu Lee, Chun-Liang Li, Chu Wang, Renshen Wang, Yasuhisa Fujii, Siyang Qin, Ashok C. Popat, Tomas Pfister

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

TabNet: Attentive Interpretable Tabular Learning.

Sercan Ö. Arik, Tomas Pfister

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

ProtoAttend: Attention-Based Prototypical Learning.

Sercan Ömer Arik, Tomas Pfister

J. Mach. Learn. Res., 2020

Interpretable Sequence Learning for COVID-19 Forecasting.

Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister

CoRR, 2020

A Simple Semi-Supervised Learning Framework for Object Detection.

Kihyuk Sohn, Zizhao Zhang, Chun-Liang Li, Han Zhang, Chen-Yu Lee, Tomas Pfister

CoRR, 2020

Differentiable Top-k Operator with Optimal Transport.

Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

CoRR, 2020

On Completeness-aware Concept-Based Explanations in Deep Neural Networks.

Chih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Tomas Pfister, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Differentiable Top-k with Optimal Transport.

Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Interpretable Sequence Learning for Covid-19 Forecasting.

Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Data Valuation using Reinforcement Learning.

Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister

Proceedings of the 37th International Conference on Machine Learning, 2020

Distance-Based Learning from Errors for Confidence Calibration.

Chen Xing, Sercan Ömer Arik, Zizhao Zhang, Tomas Pfister

Proceedings of the 8th International Conference on Learning Representations, 2020

Learning to Transfer Learn: Reinforcement Learning-Based Selection for Adaptive Transfer Learning.

Linchao Zhu, Sercan Ömer Arik, Yi Yang, Tomas Pfister

Proceedings of the Computer Vision - ECCV 2020, 2020

Consistency-Based Semi-supervised Active Learning: Towards Minimizing Labeling Cost.

Mingfei Gao, Zizhao Zhang, Guo Yu, Sercan Ömer Arik, Larry S. Davis, Tomas Pfister

Proceedings of the Computer Vision - ECCV 2020, 2020

Distilling Effective Supervision From Severe Label Noise.

Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting.

Bryan Lim, Sercan Ömer Arik, Nicolas Loeff, Tomas Pfister

CoRR, 2019

On Concept-Based Explanations in Deep Neural Networks.

Chih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Pradeep Ravikumar, Tomas Pfister

CoRR, 2019

IEG: Robust Neural Network Training to Tackle Severe Label Noise.

Zizhao Zhang, Han Zhang, Sercan Ömer Arik, Honglak Lee, Tomas Pfister

CoRR, 2019

RL-LIM: Reinforcement Learning-based Locally Interpretable Modeling.

Jinsung Yoon, Sercan Ömer Arik, Tomas Pfister

CoRR, 2019

A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels.

Yucen Luo, Jun Zhu, Tomas Pfister

CoRR, 2019

Learning to Transfer Learn.

Linchao Zhu, Sercan Ömer Arik, Yi Yang, Tomas Pfister

CoRR, 2019

Attention-Based Prototypical Learning Towards Interpretable, Confident and Robust Deep Neural Networks.

Sercan Ömer Arik, Tomas Pfister

CoRR, 2019

Harmonic Unpaired Image-to-image Translation.

Rui Zhang, Tomas Pfister, Jia Li

Proceedings of the 7th International Conference on Learning Representations, 2019

Generative Modeling for Small-Data Object Detection.

Lanlan Liu, Michael Muelly, Jia Deng, Tomas Pfister, Li-Jia Li

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Inserting Videos Into Videos.

Donghoon Lee, Tomas Pfister, Ming-Hsuan Yang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Towards Reading Hidden Emotions: A Comparative Study of Spontaneous Micro-Expression Spotting and Recognition Methods.

Xiaobai Li, Xiaopeng Hong, Antti Moilanen, Xiaohua Huang, Tomas Pfister, Guoying Zhao, Matti Pietikäinen

IEEE Trans. Affect. Comput., 2018

2017

Learning from Simulated and Unsupervised Images through Adversarial Training.

Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, Russell Webb

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Personalizing Human Video Pose Estimation.

James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Advancing human pose and gesture recognition.

Tomas Pfister

PhD thesis, 2015

Reading Hidden Emotions: Spontaneous Micro-expression Spotting and Recognition.

Xiaobai Li, Xiaopeng Hong, Antti Moilanen, Xiaohua Huang, Tomas Pfister, Guoying Zhao, Matti Pietikäinen

CoRR, 2015

Flowing ConvNets for Human Pose Estimation in Videos.

Tomas Pfister, James Charles, Andrew Zisserman

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

Automatic and Efficient Human Pose Estimation for Sign Language Videos.

James Charles, Tomas Pfister, Mark Everingham, Andrew Zisserman

Int. J. Comput. Vis., 2014

Domain-Adaptive Discriminative One-Shot Learning of Gestures.

Tomas Pfister, James Charles, Andrew Zisserman

Proceedings of the Computer Vision - ECCV 2014, 2014

Upper Body Pose Estimation with Temporal Sequential Forests.

James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman

Proceedings of the British Machine Vision Conference, 2014

Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos.

Tomas Pfister, Karen Simonyan, James Charles, Andrew Zisserman

Proceedings of the Computer Vision - ACCV 2014, 2014

2013

A Spontaneous Micro-expression Database: Inducement, collection and baseline.

Xiaobai Li, Tomas Pfister, Xiaohua Huang, Guoying Zhao, Matti Pietikäinen

Proceedings of the 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, 2013

Large-scale Learning of Sign Language by Watching TV (Using Co-occurrences).

Tomas Pfister, James Charles, Andrew Zisserman

Proceedings of the British Machine Vision Conference, 2013

Domain Adaptation for Upper Body Pose Tracking in Signed TV Broadcasts.

James Charles, Tomas Pfister, Derek R. Magee, David C. Hogg, Andrew Zisserman

Proceedings of the British Machine Vision Conference, 2013

2012

Automatic and Efficient Long Term Arm and Hand Tracking for Continuous Sign Language TV Broadcasts.

Tomas Pfister, James Charles, Mark Everingham, Andrew Zisserman

Proceedings of the British Machine Vision Conference, 2012

2011

Real-Time Recognition of Affective States from Nonverbal Features of Speech and Its Application for Public Speaking Skill Analysis.

Tomas Pfister, Peter Robinson

IEEE Trans. Affect. Comput., 2011

Differentiating spontaneous from posed facial expressions within a generic facial expression recognition framework.

Tomas Pfister, Xiaobai Li, Guoying Zhao, Matti Pietikäinen

Proceedings of the IEEE International Conference on Computer Vision Workshops, 2011

Recognising spontaneous facial micro-expressions.

Tomas Pfister, Xiaobai Li, Guoying Zhao, Matti Pietikäinen

Proceedings of the IEEE International Conference on Computer Vision, 2011

2010

Speech Emotion Classification and Public Speaking Skill Assessment.

Tomas Pfister, Peter Robinson

Proceedings of the Human Behavior Understanding, First International Workshop, 2010