Presented in Annual Meeting of the Radiological Society of North America 2018
Automatic counting and localizing in dense crowd scenes...
Thanks to the availability and...
Semantic image segmentation, assigning a label from many....
Computers have scanned aerial photographs and conducted the....
Human detection in dense crowds is an important problem, as it is a prerequisite...
Data association is an essential component of any human...
Recognition of human actions in...
In this project a new system for image localization and location recognition in terms of ...
Based on the Lagrangian framework for fluid dynamics, a streakline representation of flow...
There is a large variety of trackers, which have been proposed in the literature during the last two decades with some mixed success...
The problem that this project deals with is that of detection and tracking of large number of objects in Wide Area Surveillance (or WAS) data. WAS is aerial...
Given the very large volume of...
| Date | Description |
|---|---|
| February 22 2:00PM, Research I RM-101 | A Navigational Approach to Health by Dr. Ramesh Jain of the University of California |
| January 30 2:00PM, Creol-103 | Deep Learning, Generative Adversarial Networks and Domain Adaptation - Technologies that will Transform Clinical Research and Health Care by Dr. Rama Chellappa of the University of Maryland |
| April 10 11:00AM | Mining for Histological Footprints of Cancer by Dr. Nasir Rajpoot of the University of Warwick HEC 101 |
| Date | Description |
|---|---|
| March 29 11:00AM | What can be derived from an instance? by Dr. Arnold Smeulders of the University of Amsterdam HEC 101 |
| March 28 2:30PM | Recent Advances in Algorithms for Automatic Target Detection and Recognition by Dr. Abhijit Mahalanobis of Lockheed Martin Corporation HEC 101 |
| March 7 3:00PM | Fun Research in Computer Vision and Robotics by Dr. Takeo Kanade of Carnegie Mellon University HEC 101 |
| Feb 14 1:00PM | Vision, Brain, Computation and Attention: What You Really Need to Know by Dr. John Tsostsos of York University HEC 101 |
| Dec 15 10:30AM | Two Routes for Image-to-Image Translation: Rule-based vs. Learning-based by Dr. Minglun Gong of the Memorial University of Newfoundland HEC 450 |
| Dec 11 4:00PM | Déjà Vécu: Learning from Legacy MoCap Data for Robust Human Action Recognition by Dr. Ajmal Mian of the University of Western Australia |
| Nov 20 4:00PM | 3D-Centric Data-Driven Visual Computing by Dr. Qixing Huang of the University of Texas HEC 101 |
| Nov 2 10:00AM | Final Oral Examination of Gonzalo Vaca-Castano HEC 101B |
| Nov 3 10:00AM | Final Oral Examination of Nasim Souly HEC 101 |
| Nov 3 2:00PM | Final Oral Examination of Khurram Soomro HEC 101 |
| Oct 11 4:00PM | Human-Machine Computer Vision Systems Transferring Human Capabilities to Visual Classifiers by Dr. Concetto Spampinato of the University of Catania PS160/161 |
| August 2 11:00AM | von Mises-Fisher Mixture Model-based Deep learning and its Application to Face Verification by Dr. Liming Chen of University of Lyon, France HEC 101 |
| July 17 11:15AM | Computational Imaging by Dr. Shree Nayar of Columbia University UCF Alumni Center |
| July 6 1:30PM | Rate-invariant analysis of trajectories on Kendall shape space-applications to 3D action recognition and physical performance assessment by Dr. Boulbaba Ben Amor of Mines-Telecom Institute (IMT) Lille Douai, France HEC 119 |
| May 18 3:00PM | Towards Privacy Preserving Cameras by Dr. Sanjeev Jagannatha Koppal of University of Florida by Dr. Jean Ponce of Ecole Normale Superieure, Paris, France HEC 101 |
| Feb 16 11:00AM | General Geometric Models of Image Formation by Dr. Jean Ponce of Ecole Normale Superieure, Paris, France HEC 101 |
| Dec 9 11:00AM | From Cliques to Equilibria: Dominant-Set Clustering and Its Applications by Dr. Marcello Pelillo of Ca'Foscari University of Venice HEC 113 |
| Nov 29 11:00AM | On Advances in the Role of Differential Geometry in Computer Vision and Pattern Recognition by Dr. Anuj Srivastava of Florida State University HEC 101 |
| Nov 16 1:30PM | Feedforward and feedback processes in visual recognition by Dr. Thomas Serre of Brown University HEC 101 |
| Oct 20 4:30pm | Scale Up Video understanding with Deep Neural Networks by Mr. Chuang Gan of Tsinghua University MSB 405 |
| Sep 29 11:00am | Weekly supervised learning from images and video by Dr. Ivan Laptev of INRIA, Paris HEC 101 |
| Aug 12 3:00pm | Local Zernike Moments: A New Representation for Face Recognition by Dr. Muhittin Gokmen of MEF University, Istanbul HEC 101 |
