The 19th IEEE Workshop on Perception Beyond the Visible Spectrum (PBVS) Call for Papers

The 19th IEEE Workshop on Perception Beyond the Visible Spectrum (PBVS) 

Call for Papers
The objective of this workshop is to highlight cutting edge advances
and state-of-the-art work being made in the exponentially growing
field of PBVS (previously “Object Tracking & Classification Beyond
the Visible Spectrum” - OTCBVS) integrating sensor processing,
algorithms, and applications. PBVS 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. Advancing vision-based systems includes
frameworks and methods featured in PBVS.

The computer vision community used to focus mostly on the development
of vision algorithms for object detection, tracking, and
classification with visible range sensors in day and office-like
environments. In the last decade, infrared (IR), depth, X-ray, and
other non-visible imaging sensors were used only in special area like
medicine and defense. The relatively lower interest in those sensory
areas in comparison to traditional computer vision was due in part to
their high cost, low resolutions, poor image quality, lack of widely
available datasets, and/or lack of consideration of the advantages of
the non-visible part of the spectrum. These limitations are now being
overcome as sensor technology advances rapidly and sensor costs fall
dramatically. Furthermore, the increasing interest in autonomous
systems, where safety and reliability are a major concern, has
highlighted the importance of robust perception systems. In such
critical systems, sensors operating in different spectrums complement
each other to overcome the limitations of each individual sensor to
provide robust and reliable perception in various lighting and weather

We encourage the submission of original papers that cover the topics
of interest mentioned below. In order to develop robust and accurate
vision-based systems that operate in and beyond the visible spectrum,
not only existing methods and algorithms originally developed for the
visible range should be improved and adapted, but also entirely new
algorithms that consider the potential advantages of non-visible
ranges are certainly required. The fusion of visible and non-visible
ranges, like radar and IR images, depth images and IMU information, or
thermal and visible spectrum images as well as acoustic data, is
another dimension to explore for higher performance of vision-based

This 19th IEEE CVPR Workshop on Perception Beyond the Visible Spectrum
(PBVS’2023) fosters connections between communities in the machine
vision world ranging from public research institutes to private,
defense, and federal laboratories. PBVS brings together academic
pioneers, industrial and defense researchers and engineers in the
field of computer vision, image analysis, pattern recognition, machine
learning, signal processing, artificial intelligence, sensor
exploitation, and HCI.

PBVS'2023 challenges are: Thermal Image Super-Resolution
(TISR'2023), Multi-modal Aerial View Object Classification
(MAVOC'2023), and Semi-Supervised Hyperspectral Object Detection
(SSHODC'2023). For more information about the challenges, the
datasets, the evaluation approaches, and measures as well as the
deadline for participation, please visit the workshop website.

Topics of Interest
Sensing/Imaging Technologies
* IR/EO/RGBD imaging systems
* Underwater sensing
* Multi-spectral/Satellite imaging
* Spectroscopy/Microscopy imaging
* LIDAR/LDV sensing
* Compressive sensing
* RADAR/SAR imaging
* Radiation sensing
* Active Imaging; Cooperative Sensing
Applications & Systems
* Surveillance and reconnaissance systems
* Unmanned autonomous Systems
* Vehicle, Ship, object classification
* Robotic grasping
* Vision-aided navigation and SLAM
* Night/Shadow vision
* Sensing for agriculture and food safety
* Vision-based autonomous aerial vehicles
* Lifelong & Robust Machine Learning
Theory and Algorithms
* Deep Learning, Reinforcement Learning
* Imagery / Video exploitation
* Object / Target tracking and recognition
* Feature extraction and matching
* Activity / Pattern learning and recognition
* Multimodal / Multi-sensor / INT fusion
* Multimodal Geo-registration
* 3D Reconstruction and Shape modeling
* Automatic Caption Generation; Data Labeling

Organizer and General Chair
Riad I. Hammoud, USA
Program Chair
Michael Teutsch
Hensoldt Optronics, Germany
Program Co-Chairs
Angel D. Sappa Erhan Gundogdu
CVC, Spain; ESPOL, Amazon, Ecuador Germany
Challenge Chair
Angel D. Sappa
CVC, Spain; ESPOL Univ., Ecuador
Publication Chair
Yi Ding
Thales Group, USA
Honorary Chair
Erik Blasch
Publicity Chair
Wassim El Ahmar
University of Ottawa, Canada

Important Dates:
 Submission: March 06, 2023
 Notification: April 01, 2023
 Camera ready: April 07, 2023
 Workshop day: June 18, 2023

Website, challenge, and benchmarking data: 
Contact: or