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DTC Science and Technology Innovators Lecture Series

Deep Representations, Domain Adaptation and Adversarial Learning for Some Computer Vision Problems

by

Rama Chellappa
University of Maryland

Thursday, September 12, 2019
1:30 p.m. reception
1:45 p.m. lecture

401/402 Walter Library

Rama Chellappa

View webcast of this lecture

Recent developments in deep representation-based methods for many computer vision problems have knocked down several research themes pursued over the last four decades. In this talk, I will discuss methods based on deep representations for designing robust computer vision systems with applications in unconstrained face and action verification and recognition. The UMD face and action recognition systems are based on fusing multiple deep convolutional neural networks (DCNNs) trained using publicly available still and video face data sets and task appropriate loss functions. I will then discuss some recent results on unsupervised domain adaptation methods for object recognition and semantic segmentation using Generative Adversarial Networks (GAN). I will conclude the talk by presenting Defense-GAN, a method for improving the robustness of deep learning networks to adversarial attacks.

 

Rama Chellappa is a Distinguished University Professor, a Minta Martin Professor of Engineering and a Professor in the ECE department and the Institute for Advanced Computer Studies at University of Maryland. His current research interests span many areas in image processing, computer vision, machine learning and pattern recognition. Prof. Chellappa has received several awards from IEEE, the International Association of Pattern Recognition, the University of Southern California and the University of Maryland. He was recognized as an Outstanding Electrical and Computer Engineer by Purdue University and received the Distinguished Alumni Award from the Indian Institute of Science. He served as the Editor-in-Chief of PAMI, as a Distinguished Lecturer of the IEEE Signal Processing Society and as the President of IEEE Biometrics Council. He is a Golden Core Member of the IEEE Computer Society; He is a Fellow of IEEE, IAPR, OSA, AAAS, ACM and AAAI and holds six patents.

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