Source: https://people.epfl.ch/alexandre.alahi?lang=en
Timestamp: 2019-04-22 06:47:21+00:00

Document:
Alexandre Alahi is currently an Assistant Professor at EPFL. He spent five years at Stanford University as a Post-doc and Research Scientist after obtaining his Ph.D. from EPFL. His research enables machines to perceive the world and make decisions in the context of transportation problems and smart environments. He has worked on the theoretical challenges and practical applications of socially-aware Artificial Intelligence, i.e., systems equipped with perception and social intelligence. He was awarded the Swiss NSF early and advanced researcher grants for his work on predicting human social behavior. He won the CVPR Open Source Award (2012) for his work on Retina-inspired image descriptors, and the ICDSC Challenge Prize (2009) for his sparsity-driven algorithm that has tracked more than 100 million pedestrians to date. His research has been covered internationally by BBC, abc, PBS, Euronews, Wall street journal, and other national news outlets around the world. Alexandre has also co-founded multiple startups such as Visiosafe, and won several startup competitions. He was elected as one of the Top 20 Swiss Venture leaders in 2010.
s. Mokhtarzadeh; M. Ghadimi; A. Nickabadi; A. Alahi : Convolutional Relational Machine for Group Activity Recognition. 2019-06. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
S. Kreiss; L. Bertoni; A. Alahi : PifPaf: Composite Fields for Human Pose Estimation. 2019-06. IEEE conference on computer vision and pattern recognition (CVPR).
s. Yeung; F. Rinaldo; J. Jopling; B. Liu; R. Mehra et al. : A Computer Vision System to Detect Bedside Patient Mobilization; Nature Digital Medicine. 2019-03-01.
Y. Liu; P. A. Kothari; A. Alahi : Collaborative GAN Sampling. 2019-02-11.
A. Maksai : Training Algorithms for Multiple Object Tracking. Lausanne, EPFL, 2019. DOI : 10.5075/epfl-thesis-9203.
C. Chen; Y. Liu; S. Kreiss; A. Alahi : Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning. 2019. International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 20-24, 2019.
B. Sifringer; V. Lurkin; A. Alahi : Let Me Not Lie: Learning MultiNomial Logit; arxiv. 2018-12-23.
B. Sifringer; V. Lurkin; A. Alahi : Enhancing Discrete Choice Models with Neural Networks. 2018-09-05. hEART 2018 – 7th Symposium of the European Association for Research in Transportation conference, Athens, September 5-7, 2018.
G. Adaimi; A. Alahi : Learning nuisances to track pedestrians in autonomous vehicles. 2018-09-05. Heart 2018 - 7th Symposium of the European Association for Research in Transportation conference, Athens, September 5-7, 2018.
B. Schroeder; A. Alahi : Using A Priori Knowledge to Improve Scene Understanding in Autonomous Navigation. 2018-09-05. Heart 2018 - 7th Symposium of the European Association for Research in Transportation conference, Athens, September 5-7, 2018.
P. Coscia; L. Ballan; F. Palmieri; A. Alahi; S. Savarese : Linear Artificial Forces for Human Dynamics in Complex Contexts. 2018-06-15. WIRN, Vietri, 13-15 june 2018.
G. Adaimi; A. Alahi : Learning nuisances to track pedestrians in autonomous vehicles. 2018-05-16. 18th Swiss Transport Research Conference, Monte Verità, Ascona, May 16 – 18, 2018.
R. A. F. Lamotte : Congestion and departure time choice equilibrium in urban road networks. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8862.
S. Zhang : Micro-mechanical finite element modeling for in-plane behavior of historical masonry. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8792.
A. Sadeghian; F. Legros; M. Voisin; R. Vesel; A. Alahi et al. : CAR-Net: Clairvoyant Attentive Recurrent Network. 2018. European Conference on Computer Vision (ECCV), Munich, 8-14 September 2018.
T. Bagautdinov : Variational Methods for Human Modeling. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8680.
P. Coscia; F. Castaldo; F. Palmieri; A. Alahi; S. Savarese et al. : Long-term path prediction in urban scenarios using circular distributions; Image and Vision Computing. 2018. DOI : 10.1016/j.imavis.2017.11.006.
A. Gupta; j. Johnson; l. Fei-Fei; S. Savarese; A. Alahi : Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks. 2018. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt lake city, June 18-22.
A. Fernández Antolín : Dealing with Correlations in Discrete Choice Models. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8170.
G. Bianconi; R. Mehra; S. Yeung; F. Salipur; J. Jopling et al. : Vision-Based Prediction of ICU Mobility Care Activities using Recurrent Neural Networks ; NIPS workshop on Machine Learning for Health, 2017-12-08.
M. Guo; A. Haque; s. Yeung; J. Jopling; L. Downing et al. : Viewpoint Invariant Convolutional Networks for Identifying Risky Hand Hygiene Scenarios ; Workshop at NIPS on Machine Learning for Health.
A. Alahi; J. Wilson; L. Fei-Fei; S. Savarese : Unsupervised Camera Localization in Crowded Spaces. 2017. IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 29 - June 3, 2017.
A. Alahi; V. Ramanathan; K. Goel; A. Robicquet; A. Sadeghian et al. : Learning to Predict Human Behavior in Crowded Scenes; Group and Crowd Behavior for Computer Vision; Elsevier, 2017. p. 183-207.
A. Alahi; V. Ramanathan; L. Fei-Fei : Tracking millions of humans; Group and Crowd Behavior for Computer Vision; Elsevier, 2017. p. 115-135.
K. Nakamura; S. Yeung; A. Alahi; L. Fei-Fei : Jointly Learning Energy Expenditures and Activities using Egocentric Multimodal Signals. 2017. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, USA, July 21-26, 2017.
T. Bagautdinov; A. Alahi; F. Fleuret; P. Fua; S. Savarese : Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition. 2017. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, USA, July 21-26, 2017. p. 3425-3434. DOI : 10.1109/Cvpr.2017.365.
Z. Luo; B. Peng; D.-A. Huang; A. Alahi; L. Fei-Fei : Unsupervised Learning of Long-Term Motion Dynamics for Videos. 2017. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, USA, July 21-26, 2017.
A. Haque; M. Guo; A. Alahi; S. Yeung; Z. Luo et al. : Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance. 2017. Machine Learning for Healthcare (MLHC), Northeastern University, Massachusetts, August 18- 19, 2017.
A. Gupta; J. Johnson; A. Alahi; L. Fei-Fei : Characterizing and Improving Stability in Neural Style Transfer. 2017. International Conference on Computer Vision (ICCV), Venice, Italy, October 22-29, 2017.
A. Sadeghian; A. Alahi; S. Savarese : Tracking The Untrackable: Learning To Track Multiple Cues with Long-Term Dependencies. 2017. International Conference on Computer Vision (ICCV), Venice, Italy, October 22-29, 2017.
S. Yeung; A. Alahi; A. Haque; Z. Luo; B. Peng et al. : Vision-Based Hand Hygiene Monitoring in Hospitals ; American Medical Informatics Association (AMIA) Symposium, 2016.
A. Alahi; K. Goel; V. Ramanathan; A. Robicquet; L. Fei-Fei et al. : Social LSTM: Human Trajectory Prediction in Crowded Spaces. 2016. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 27-30 June 2016. p. 961-971. DOI : 10.1109/CVPR.2016.110.
A. Haque; A. Alahi; L. Fei-Fei : Recurrent Attention Models for Depth-Based Person Identification. 2016. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 27-30 June, 2016. p. 1229-1238. DOI : 10.1109/CVPR.2016.138.
P. Coscia; F. Castaldo; F. A. N. Palmieri; L. Ballan; A. Alahi et al. : Point-based Path Prediction from Polar Histograms. 2016. p. 1961-1967.
A. Robicquet; A. Sadeghian; A. Alahi; S. Savarese : Learning Social Etiquette: Human Trajectory Understanding In Crowded Scenes. 2016. p. 549-565. DOI : 10.1007/978-3-319-46484-8_33.
A. Haque; B. Peng; Z. Luo; A. Alahi; S. Yeung et al. : Towards Viewpoint Invariant 3D Human Pose Estimation. 2016. p. 160-177. DOI : 10.1007/978-3-319-46448-0_10.
L. Ballan; F. Castaldo; A. Alahi; F. Palmieri; S. Savarese : Knowledge Transfer for Scene-specific Motion Prediction. 2016. European Conference on Computer Vision (ECCV). p. 697-713. DOI : 10.1007/978-3-319-46448-0_42.
J. Johson; A. Alahi; L. Fei-Fei : Perceptual Losses for Real-Time Style Transfer and Super-Resolution. 2016. European Conference on Computer Vision (ECCV). p. 694-711. DOI : 10.1007/978-3-319-46475-6_43.
Y. Xiang; A. Alahi; S. Savarese : Learning to Track: Online Multi-object Tracking by Decision Making. 2015. IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 7-13 December 2015. p. 4705-4713. DOI : 10.1109/ICCV.2015.534.
A. Alahi; A. Haque; L. Fei-Fei : RGB-W: When Vision Meets Wireless. 2015. IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 7-13 December 2015. p. 3289-3297. DOI : 10.1109/ICCV.2015.376.
A. Alahi; G. Goetz; E. D’Angelo : Biologically Inspired Keypoints; Biologically Inspired Computer Vision: Fundamentals and Applications; Wiley, 2015. p. 347-374.
A. Alahi; V. Ramanathan; L. Fei-Fei : Socially-Aware Large-Scale Crowd Forecasting. 2014. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, OH, USA, 23-28 June 2014. p. 2211-2218. DOI : 10.1109/CVPR.2014.283.
A. Alahi : Vision-Based Scene Understanding with Sparsity Promoting Priors. Lausanne, EPFL, 2011. DOI : 10.5075/epfl-thesis-5070.
A. Azarbayejani; A. Alahi; M. Erdem ; System and Method for Measuring Performances of Surveillance Systems. US7415385 ; JP2008165740 ; US2008126031 . 2008.
A. Alahi; M. Bierlaire; M. Kunt : Combination of Fixed and Mobile Cameras for Automatic Pedestrian Detection. 2008.
A. Alahi; M. Bierlaire; M. Kunt : Object Detection and Matching with Mobile Cameras Collaborating with Fixed Cameras. 2008. European Conference on Computer Vision, Marseille, France, October 18, 2008.
A. Alahi; D. Marimon; M. Bierlaire; M. Kunt : A Master-Slave Approach for Object Detection and Matching with Fixed and Mobile Cameras. 2008. 15th IEEE International Conference on Image Processing, San Diego, USA, October 12-15, 2008. p. 1712-1715. DOI : 10.1109/ICIP.2008.4712104.
We work on the theoretical challenges and practical applications of socially-aware systems, i.e., machines that can not only perceive human behavior, but reason with social intelligence in the context of transportation problems and smart spaces.
We envision a future where intelligent machines are ubiquitous, where self-driving cars, delivery robots, and self-moving Segways are facts of everyday life. Beyond embodied agents, we will also see our living spaces – our homes, buildings, and cities – become equipped with ambient intelligence which can sense and respond to human behavior. However, to realize this future, intelligent machines need to develop social intelligence and the ability to make safe and consistent decisions in unconstrained crowded social scenes. Self-driving vehicles must learn social etiquette in order to navigate cities like Paris or Naples. Social robots need to comply with social conventions and obey (unwritten) common-sense rules to effectively operate in crowded terminals. For instance, they need to respect personal space, yield right-of-way, and “read” the behavior of others to predict future actions.
Our research is centered around understanding and predicting human social behavior with multi-modal visual data. Our work spans multiple aspects of socially-aware systems: from 1- collecting multi-modal data at scale, 2- Extracting coarse-to-fine grained behaviours in real-time, 3- designing deep learning methods that can learn to predict human social behavior in a fully data-driven way, to 4- integrating the developed methods in real-world systems such as a vehicle or a socially-aware robot that navigates crowded social scenes.

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