Dates currently being confirmed; check back.

Call for Papers Announced 2 May
Journal-first (JIST/JPI) Submissions

∙ Submission site Opens 2 May 
∙ Journal-first (JIST/JPI) Submissions Due 1 Aug
∙ Final Journal-first manuscripts due 28 Oct
Conference Papers Submissions
∙ Abstract Submission Opens 1 June
∙ Priority Decision Submission Ends 15 July
∙ Extended Submission Ends  19 Sept
∙ FastTrack Conference Proceedings Manuscripts Due 25 Dec 
∙ All Outstanding Proceedings Manuscripts Due
 6 Feb 2023
Registration Opens 1 Dec
Demonstration Applications Due 19 Dec
Early Registration Ends 18 Dec

Hotel Reservation Deadline 6 Jan
Symposium begins
15 Jan

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Image Processing: Algorithms and Systems XXI

Monday 16 January 2023

10:20 – 10:50 AM Coffee Break

12:30 – 2:00 PM Lunch

Monday 16 January PLENARY: Neural Operators for Solving PDEs

Session Chair: Robin Jenkin, NVIDIA Corporation (United States)
2:00 PM – 3:00 PM
Cyril Magnin I/II/III

Deep learning surrogate models have shown promise in modeling complex physical phenomena such as fluid flows, molecular dynamics, and material properties. However, standard neural networks assume finite-dimensional inputs and outputs, and hence, cannot withstand a change in resolution or discretization between training and testing. We introduce Fourier neural operators that can learn operators, which are mappings between infinite dimensional spaces. They are independent of the resolution or grid of training data and allow for zero-shot generalization to higher resolution evaluations. When applied to weather forecasting, neural operators capture fine-scale phenomena and have similar skill as gold-standard numerical weather models for predictions up to a week or longer, while being 4-5 orders of magnitude faster.

Anima Anandkumar, Bren professor, California Institute of Technology, and senior director of AI Research, NVIDIA Corporation (United States)


Anima Anandkumar is a Bren Professor at Caltech and Senior Director of AI Research at NVIDIA. She is passionate about designing principled AI algorithms and applying them to interdisciplinary domains. She has received several honors such as the IEEE fellowship, Alfred. P. Sloan Fellowship, NSF Career Award, and Faculty Fellowships from Microsoft, Google, Facebook, and Adobe. She is part of the World Economic Forum's Expert Network. Anandkumar received her BTech from Indian Institute of Technology Madras, her PhD from Cornell University, and did her postdoctoral research at MIT and assistant professorship at University of California Irvine.

3:00 – 3:30 PM Coffee Break

EI 2023 Highlights Session

Session Chair: Robin Jenkin, NVIDIA Corporation (United States)
3:30 – 5:00 PM
Cyril Magnin II

Join us for a session that celebrates the breadth of what EI has to offer with short papers selected from EI conferences.

NOTE: The EI-wide "EI 2023 Highlights" session is concurrent with Monday afternoon COIMG, COLOR, IMAGE, and IQSP conference sessions.


Evaluation of image quality metrics designed for DRI tasks with automotive cameras, Valentine Klein, Yiqi LI, Claudio Greco, Laurent Chanas, and Frédéric Guichard, DXOMARK (France) [view abstract]


Human performance using stereo 3D in a helmet mounted display and association with individual stereo acuity, Bonnie Posselt, RAF Centre of Aviation Medicine (United Kingdom) [view abstract]


Smartphone-enabled point-of-care blood hemoglobin testing with color accuracy-assisted spectral learning, Sang Mok Park1, Yuhyun Ji1, Semin Kwon1, Andrew R. O’Brien2, Ying Wang2, and Young L. Kim1; 1Purdue University and 2Indiana University School of Medicine (United States) [view abstract]


Designing scenes to quantify the performance of automotive perception systems, Zhenyi Liu1, Devesh Shah2, Alireza Rahimpour2, Joyce Farrell1, and Brian Wandell1; 1Stanford University and 2Ford Motor Company (United States) [view abstract]


Visualizing and monitoring the process of injection molding, Christian A. Steinparz1, Thomas Mitterlehner2, Bernhard Praher2, Klaus Straka1,2, Holger Stitz1,3, and Marc Streit1,3; 1Johannes Kepler University, 2Moldsonics GmbH, and 3datavisyn GmbH (Austria) [view abstract]


Commissioning the James Webb Space Telescope, Joseph M. Howard, NASA Goddard Space Flight Center (United States) [view abstract]


Critical flicker frequency (CFF) at high luminance levels, Alexandre Chapiro1, Nathan Matsuda1, Maliha Ashraf2, and Rafal Mantiuk3; 1Meta (United States), 2University of Liverpool (United Kingdom), and 3University of Cambridge (United Kingdom) [view abstract]


Physics guided machine learning for image-based material decomposition of tissues from simulated breast models with calcifications, Muralikrishnan Gopalakrishnan Meena1, Amir K. Ziabari1, Singanallur Venkatakrishnan1, Isaac R. Lyngaas1, Matthew R. Norman1, Balint Joo1, Thomas L. Beck1, Charles A. Bouman2, Anuj Kapadia1, and Xiao Wang1; 1Oak Ridge National Laboratory and 2Purdue University (United States) [view abstract]


Layered view synthesis for general images, Loïc Dehan, Wiebe Van Ranst, and Patrick Vandewalle, Katholieke University Leuven (Belgium) [view abstract]


A self-powered asynchronous image sensor with independent in-pixel harvesting and sensing operations, Ruben Gomez-Merchan, Juan Antonio Leñero-Bardallo, and Ángel Rodríguez-Vázquez, University of Seville (Spain) [view abstract]


Color blindness and modern board games, Alessandro Rizzi1 and Matteo Sassi2; 1Università degli Studi di Milano and 2consultant (Italy) [view abstract]


5:00 – 6:15 PM EI 2023 All-Conference Welcome Reception (in the Cyril Magnin Foyer)

Tuesday 17 January 2023

10:00 AM – 7:30 PM Industry Exhibition - Tuesday (in the Cyril Magnin Foyer)

10:20 – 10:50 AM Coffee Break

12:30 – 2:00 PM Lunch

Tuesday 17 January PLENARY: Embedded Gain Maps for Adaptive Display of High Dynamic Range Images

Session Chair: Robin Jenkin, NVIDIA Corporation (United States)
2:00 PM – 3:00 PM
Cyril Magnin I/II/III

Images optimized for High Dynamic Range (HDR) displays have brighter highlights and more detailed shadows, resulting in an increased sense of realism and greater impact. However, a major issue with HDR content is the lack of consistency in appearance across different devices and viewing environments. There are several reasons, including varying capabilities of HDR displays and the different tone mapping methods implemented across software and platforms. Consequently, HDR content authors can neither control nor predict how their images will appear in other apps.

We present a flexible system that provides consistent and adaptive display of HDR images. Conceptually, the method combines both SDR and HDR renditions within a single image and interpolates between the two dynamically at display time. We compute a Gain Map that represents the difference between the two renditions. In the file, we store a Base rendition (either SDR or HDR), the Gain Map, and some associated metadata. At display time, we combine the Base image with a scaled version of the Gain Map, where the scale factor depends on the image metadata, the HDR capacity of the display, and the viewing environment.

Eric Chan, Fellow, Adobe Inc. (United States)


Eric Chan is a Fellow at Adobe, where he develops software for editing photographs. Current projects include Photoshop, Lightroom, Camera Raw, and Digital Negative (DNG). When not writing software, Chan enjoys spending time at his other keyboard, the piano. He is an enthusiastic nature photographer and often combines his photo activities with travel and hiking.

Paul M. Hubel, director of Image Quality in Software Engineering, Apple Inc. (United States)


Paul M. Hubel is director of Image Quality in Software Engineering at Apple. He has worked on computational photography and image quality of photographic systems for many years on all aspects of the imaging chain, particularly for iPhone. He trained in optical engineering at University of Rochester, Oxford University, and MIT, and has more than 50 patents on color imaging and camera technology. Hubel is active on the ISO-TC42 committee Digital Photography, where this work is under discussion, and is currently a VP on the IS&T Board. Outside work he enjoys photography, travel, cycling, coffee roasting, and plays trumpet in several bay area ensembles.

3:00 – 3:30 PM Coffee Break

5:30 – 7:00 PM EI 2023 Symposium Demonstration Session (in the Cyril Magnin Foyer)

Wednesday 18 January 2023

10:00 AM – 3:30 PM Industry Exhibition - Wednesday (in the Cyril Magnin Foyer)

10:20 – 10:50 AM Coffee Break

12:30 – 2:00 PM Lunch

Wednesday 18 January PLENARY: Bringing Vision Science to Electronic Imaging: The Pyramid of Visibility

Session Chair: Andreas Savakis, Rochester Institute of Technology (United States)
2:00 PM – 3:00 PM
Cyril Magnin I/II/III

Electronic imaging depends fundamentally on the capabilities and limitations of human vision. The challenge for the vision scientist is to describe these limitations to the engineer in a comprehensive, computable, and elegant formulation. Primary among these limitations are visibility of variations in light intensity over space and time, of variations in color over space and time, and of all of these patterns with position in the visual field. Lastly, we must describe how all these sensitivities vary with adapting light level. We have recently developed a structural description of human visual sensitivity that we call the Pyramid of Visibility, that accomplishes this synthesis. This talk shows how this structure accommodates all the dimensions described above, and how it can be used to solve a wide variety of problems in display engineering.

Andrew B. Watson, chief vision scientist, Apple Inc. (United States)


Andrew Watson is Chief Vision Scientist at Apple, where he leads the application of vision science to technologies, applications, and displays. His research focuses on computational models of early vision. He is the author of more than 100 scientific papers and 8 patents. He has 21,180 citations and an h-index of 63. Watson founded the Journal of Vision, and served as editor-in-chief 2001-2013 and 2018-2022. Watson has received numerous awards including the Presidential Rank Award from the President of the United States.

3:00 – 3:30 PM Coffee Break

KEYNOTE: Systematic Data Labeling (W3.1)

Session Chairs: Karen Egiazarian, Tampere University (Finland) and Atanas Gotchev, Tampere University (Finland)
3:30 – 4:15 PM
Cyril Magnin III

Conference Welcome

KEYNOTE: Systematic data labeling at the point of ingestion in enterprise systems, Gevorg Karapetyan, Zero Cognitive Systems (United States) [view abstract]

Gevorg Karapetyan is co-founder and Chief Technology Officer with Zero Cognitive Systems. In this role Karapetyan leads long-term technology vision and is responsible for the direction, coordination, and delivery of technology. Founded in 2015 in Los Gatos, California, Zero is dedicated to applying artificial intelligence and smart automation to the most pressing operational challenges of the professional services industry. Karapetyan previously worked at Imagenomic as a Senior Software Engineer and attended National Polytechnic University of Armenia. Karapetyan holds a PhD in Computer Science and has more than 10 years of experience in developing intelligent automation systems.


Machine Learning for Image Processing (W3.2)

Session Chairs: Karen Egiazarian, Tampere University (Finland) and Atanas Gotchev, Tampere University (Finland)
4:15 – 5:35 PM
Cyril Magnin III

ORCA: An end-to-end video object removal framework with cropping interested region and quality assessment, Minseong Son, Hansol Lee, Sungkeun Kwak, and Jihwan Woo, CJOliveNetworks (Republic of Korea) [view abstract]


Detection of object throwing behavior in surveillance videos, Ivo P.C. Kersten, Erkut Akdag, Egor Bondarev, and Peter H. de With, Eindhoven University of Technology (the Netherlands) [view abstract]


Hybrid diffractive optics (DOE & refractive lens) for broadband EDoF imaging, SeyyedReza MiriRostami, Samuel Pinilla, Igor Shevkunov, Vladimir Katkovnik, and Karen Egiazarian, Tampere University (Finland) [view abstract]


Evaluating active learning for blind imbalanced domains, Hiroshi Kuwajima1, Masayuki Tanaka2, and Masatoshi Okutomi2; 1DENSO Corporation and 2Tokyo Institute of Technology (Japan) [view abstract]


5:30 – 7:00 PM EI 2023 Symposium Interactive (Poster) Paper Session (in the Cyril Magnin Foyer)

5:30 – 7:00 PM EI 2023 Meet the Future: A Showcase of Student and Young Professionals Research (in the Cyril Magnin Foyer)

Image Processing: Algorithms and Systems XXI Interactive (Poster) Paper Session (W4)

5:35 – 7:00 PM
Cyril Magnin Foyer

The following work will be presented at the EI 2023 Symposium Interactive (Poster) Paper Session.

MLExchange: An integrated platform for scientific machine learning, Guanhua Hao1, Tanny Chavez1, Zhuowen Zhao1, Elizabeth Holman1, Eric Roberts1, Howard Yanxon2, Adam Green1, Harinarayan Krishnan1, Dylan McReynolds1, Nicholas Schwarz2, Petrus Zwart1, Alexander Hexemer1, and Dilworth Parkinson1; 1Lawrence Berkeley National Laboratory and 2Argonne National Laboratory (United States) [view abstract]


Thursday 19 January 2023

Face and Facial Image Processing (R1)

Session Chairs: Karen Egiazarian, Tampere University (Finland) and Atanas Gotchev, Tampere University (Finland)
8:50 – 9:50 AM
Cyril Magnin III

Facial expression recognition using visual transformer with histogram of oriented gradients, Jieun Kim, Ju o Kim, Seungwan Je, and Deokwoo Lee, Keimyung University (Republic of Korea) [view abstract]


Face expressions understanding by geometrical characterization of deep human faces representation, Adrien Raison, Theo Biardeau, Pascal Bourdon, and David Helbert, University de Poitiers (France) [view abstract]


Crowd counting using deep learning based head detection, Maryam Hassan1, Farhan Hussain1, Sultan D. Khan2, Mohib Ullah3, Mudassar Yamin3, and Habib Ullah4; 1NUST College of Electrical & Mechanical Engineering (Norway), 2National University of Technology (Pakistan), 3Norwegian University of Science and Technology (Norway), and 4Norwegian University of Life Sciences (NMBU) (Norway) [view abstract]


10:20 – 10:50 AM Coffee Break

KEYNOTE: Vulnerability of Neural Networks (R2.1)

Session Chairs: Karen Egiazarian, Tampere University (Finland) and Atanas Gotchev, Tampere University (Finland)
10:50 – 11:30 AM
Cyril Magnin III

KEYNOTE: Surprising vulnerability of neural networks: Recovering training and input data in federated learning and split computing, Pavlo Molchanov, NVIDIA Corporation (United States) [view abstract]

Pavlo Molchanov obtained his PhD (2014) from Tampere University of Technology, Finland, in the area of signal processing. His dissertation focused on designing automatic target recognition systems for radars. Since 2015 he has been with the Learning and Perception Research team at NVIDIA, currently holding a senior research scientist position. His research is focused on methods for neural network acceleration, and designing novel human-computer interaction systems and human understanding. On network acceleration, he is interested in neural network pruning methods and conditional inference. For human understanding he is working on landmark estimation, gesture recognition, hand pose estimation.


Segmentation, Classification, and Tracking (R2.2)

Session Chairs: Karen Egiazarian, Tampere University (Finland) and Atanas Gotchev, Tampere University (Finland)
11:30 AM – 12:30 PM
Cyril Magnin III

Exploring effects of colour and image quality in semantic segmentation (JIST-first), Kanjar De, Luleå University of Technology (Sweden) [view abstract]


ILIAC: Efficient classification of degraded images using knowledge distillation with cutout data augmentation, Dinesh Daultani1, Masayuki Tanaka1, Masatoshi Okutomi1, and Kazuki Endo2; 1Tokyo Institute of Technology and 2Teikyo Heisei University (Japan) [view abstract]


AInBody: Are you in shape? - An integrated deep learning model that tracks your body measurement, Nakyung Lee, Youngsun Cho, Minseong Son, Sungkeun Kwak, and Jihwan Woo, CJ OliveNetworks (Republic of Korea) [view abstract]


12:30 – 2:00 PM Lunch

Biomedical Image Processing (R3)

Session Chairs: Karen Egiazarian, Tampere University (Finland) and Atanas Gotchev, Tampere University (Finland)
2:00 – 3:00 PM
Cyril Magnin III

Deep learning based speech emotion recognition for Parkinson patient, Habib Khan1, Mohib Ullah2, Fadi Al-Machot3, Faouzi Alaya Cheikh2, and Muhammad Sajjad2; 1Islamia College University Peshawar (Pakistan), 2Norwegian University of Science and Technology (Norway), and 3Norwegian University of Life Sciences (Norway) [view abstract]


Blind denoising of dental X-ray images, Mykola Ponomarenko1, Oleksandr Miroshnichenko2, Vladimir Lukin2, Sergey Krivenko2, and Karen Egiazarian1; 1Tampere University (Finland) and 2National Aerospace University (Ukraine) [view abstract]


Automatic estimation of mucosal waves lateral peak sharpness – Modern approach, Ales Zita1, Simon Gresko1, Adam Novozamsky1, Michal Sorel1, Barbara Zitova1, Jan Svec2, and Jitka Vydrova3; 1Institute of Information Theory and Automation, 2Palacky University, and 3Voice Centre Prague, Medical Healthcom, Ltd (Czechia) [view abstract]


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