About This Workshop Series
The PBVS (previously OTCBVS) workshop is to highlight cutting edge advances and state-of-the-art work being made in the exponentially growing field of PBVS along its three main axes: Sensing/Imaging Technologies, Applications and Systems , and Theory/Algorithms. This field involves deep theoretical research in sub-areas of image processing, machine vision, pattern recognition, machine learning, robotics, and augmented reality within and beyond the visible spectrum. It also presents a suitable framework for building solid advanced vision based systems.
Previous PBVS(OTCBVS) Workshops
Previous Keynote Speakers
Firooz Sadjadi
Lockheed Martin Corp, USA
"Polarimetric Object Classification"
Mohan M. Trivedi
UC San Diego, USA
"Observing Humans in Smart Spaces: A Multi Perspective and Multi Modal Approach"
Lawrence B. Wolff
Equinox Corporation, USA
"Making The Most of Multi-Modal Image Fusion"
Vassilios Morellas
University of Minnesota, USA
"Video Analytics for Security and Transportation Applications"
Nasser M. Nasrabadi
US Army Research Laboratory, USA
"Target detection and recognition in hyperspectral imagery"
Mubarak Shah
University of Central Florida, USA
"An Overview of Visual Tracking in EO and IR Imagery"
Rama Chellappa
University of Maryland, USA
"Object Detection, Tracking and Identification Using Hyperspectral Video"
Aly A. Farag
University of Louisville, USA
"Interceptors & Simulated Cool Target Tracking"
Aswin C. Sankaranarayanan
Carnegie Mellon University, USA
"Compressive Video Sensing"
Robert T. Collins
The Pennsylvania State University, USA
"Multi-frame Data Association with Higher-Order Cost Functions"
Ko Nishino
Drexel University, USA
"Visual Material Recognition"
Erik Blasch
Air Force Research Lab, USA
"Computer Vision Augmented with High-Level Information Fusion"
Margrit Betke
Boston University, USA
"Analyzing the Flight Behavior of Bats in Thermal Infrared Video"
John M Irvine
Charles Stark Draper Laboratory, USA
"Towards a Unified Understanding of Image Quality: Quantifying Spatial, Temporal, and Spectral Information for Computer Vision"
Guna Seetharaman
Air Force Research Laboratory, USA
"3D Assisted Common Operational Framework"
Erik Learned-Miller
University of Massachusetts, Amherst, USA
"Multi-view CNNs, Invisible-Object Segmentation, and Cross Quality Distillation: 3 new methods and their relation to PBVS"
Jon Barker
NVIDIA Corporation, USA
"Applying GPU-accelerated Deep Learning beyond the visible spectrum"
Behzad Kamgar-Parsi
Office of Naval Research, USA
"A Decade of Progress in Computer Vision"
Kevin Priddy
Air Force DCGS, USA
"The Hype, Hope and Promise of Learning Machines"
Jingyi Yu
University of Delaware, USA
"Towards Ultimate Plenoptic Imaging"
Leo Tam
NVIDIA Corporation, USA
"Practical Deep Learning: Studies from Medical Imaging"
Ian Goodfellow
Google Brain, USA
"Generative Adversarial Networks"
Dimitris G. Manolakis
MIT Lincoln Laboratory, USA
"Hyperspectral Imaging Remote Sensing: Progress and Challenges"
Sabine Süsstrunk
EPFL, Switzerland
"RGB+: Using Near-Infrared (NIR) to improve Computational Photography Applications"
David R. Thompson
NASA JPL/CalTech, USA
"Imaging Spectroscopy for Earth and Planetary Science"
Pierre Boulanger
FLIR Systems, USA
"CNN with Long Ware Infrared cameras in various of applications"
Amir R. Zamir
Stanford & UC Berkeley, USA
"Transfer Learning for Multi-Task Perception and Robotics"
Michael Felsberg
Linköping University, Sweden
"Learning to Analyze what is Beyond the Visible Spectrum"
Le Lu
PAII Inc, USA
"Multi-phase CT Imaging+AI Enabled Deep Precision Medicine Solutions for Pancreatic Cancer: Multi-institutional Screening, Precision Diagnosis and Prognosis"
Kilian Weinberger
Cornell University, USA
"Deep Learning with Depth Perception - Representation Matters"
Volkan Cevher
Swiss Federal Institute of Technology in Lausanne, Switzerland
"Adversarial machine learning: Recent developments"
Dinggang Shen
School of BME, ShanghaiTech University, China
"AI based Medical Image Reconstruction"
Al Bovik
University of Texas at Austin, USA
"Picture Quality Prediction Outside the Visible Spectrum"
Matt Turek
DARPA, USA
"Media Authentication and Explainable AI: Applications Beyond the Visible Spectrum"