Journal-first submissions deadline
8 Aug
Priority submissions deadline 30 Jul
Final abstract submissions deadline 15 Oct
Manuscripts due for FastTrack publication
30 Nov

Early registration ends 31 Dec

Short Courses
11-14 Jan
Symposium begins
17 Jan
All proceedings manuscripts due
31 Jan
Bronze Level



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Join us for the Symposium-wide Interactive (Poster) Papers Session

The following papers have been accepted for interactive (poster) presentation as of 3 January2022.

The Symposium Interactive (Poster) Papers Session will be held on Day 3:
19 January: 08:20 San Francisco / 11:20 New York / 17:20 Paris     20 January: 01:20 Tokyo

Computational Imaging XX

P-01: Face beauty prediction through deep discriminant mapping, Fadi Dornaika1, Abdelmalik Moujahid1, Kunwei Wang1; 1University of the Basque Country, San Sebastian, Spain.

P-02: Improvement of aerial image by simulations, Katsunari Ashimine1, Munemitsu Abe1, Kazuhiro Wako2; 1Alps Alpine Co., Ltd., Iwaki, Fukushima, Japan; 2National Institute of Technology, Sendai College, Natori, Miyagi, Japan.

Computer Vision and Image Analysis of Art 2022

P-03: Artist-specific style transfer for deep net semantic segmentation of paintings: The value of large corpora of surrogate artworks, Matthias Wödlinger1, Thomas Heitzinger1, David G. Stork2; 1TU Wien, Vienna, Austria; 2Consultant, Portola Valley, CA, United States.

The Engineering Reality of Virtual Reality 2022

P-04: Data visualization of crime data using immersive virtual reality, Sharad Sharma1; 1Bowie State University, Bowie, MD, United States.

Human Vision and Electronic Imaging 2022

P-05: A simple and efficient deep scanpath prediction, Mohamed A. Kerkouri1, Aladine Chetouani1; 1Université d'Orléans, Orléans, France.

P-06: INDeeD: Identical and disparate feature decomposition from multi-label data, Tserendorj Adiya1, Seungkyu Lee1; 1Kyung Hee University, Yongin, South Korea.

P-07: On phenomenal visual space geometry, Jacek Turski1; 1University of Houston-Downtown, Houston, TX, United States.

Image Processing: Algorithms and Systems XX

P-08: Class specific biased extrapolation of images in latent space for imbalanced image classification, Suhyeon Jeong1, Seungkyu Lee1; 1Kyung Hee University, Yongin, South Korea.

P-09: Computer vision-based classification of schizophrenia patients from retinal imagery, Diana Joseph1, Adriann Lai1, Steven Silverstein1, Rajeev Ramchandran1, Edgar Bernal1; 1University of Rochester, Rochester, NY, United States.

P-10: Optimal parameters selection of the Frost filter based on despeckling efficiency prediction for Sentinel SAR images, Oleksii S. Rubel1, Andrii S. Rubel1, Vladimir Lukin1, Karen Egiazarian2; 1National Aerospace University, Kharkiv, Ukraine; 2Tampere University, Tampere, Finland.

P-11: Simulation-based virtual reality training for firefighters, Mohamed Saifeddine Hadj Sassi1, Federica Battisti2, Marco Carli1; 1Roma Tre University, Rome, Italy; 2University of Padova, Padova, Italy.

Image Quality and System Performance XIX

P-12: Image quality performance of CMOS image sensor equipped with CMY color filter in mobile devices, Sungho Cha1; 1Samsung Electronics Co, Ltd., Hwaseong, South Korea.

P-13: Visualization for texture analysis of the Shitsukan Research Database based on luminance information, Norifumi Kawabata1; 1Hokkaido University, Sapporo, Japan.

Imaging Sensors and Systems 2022

P-14: Capture optimization for composite images, Henry G. Dietz1, Dillon Abney1; 1University of Kentucky, Lexington, KY, United States.

P-15: DePhaseNet: A deep convolutional network using phase differentiated layers and frequency based custom loss for RGBW image sensor demosaicing, Irina Kim1, Youngil Seo1, Dongpan Lim1, Jeongguk Lee1, Wooseok Choi1, Seongwook Song1; 1Samsung Electronics Co., Ltd., Hwaseong, Gyeonggi-do, South Korea.

P-16: The study and analysis of using CMY color filter arrays for 0.8 mm CMOS image sensors, Pohsiang Wang1, An-Li Kuo1, Ta-Yung Ni1, Hao-Wei Liu1, Yu C. Chang1, Ching-Chiang Wu1, Ken Wu1; 1VisEra Technologies, Hsinchu City, East District, Taiwan.

Machine Learning for Scientific Imaging 2022

P-17: Advantage of machine learning over maximum likelihood in limited-angle low-photon x-ray tomography,  Zhen Guo1Jung Ki Song1George Barbastathis1Michael A. Glinsky2Courtenay T. Vaughan2Kurt W. Larson2Bradley K. Alpert3, and Zachary H. Levine41Massachusetts Institute of Technology, 2Sandia National Laboratory, 3Applied and Computational Mathematics Division, National Institute of Standards and Technology, and 4Quantum Measurement Division, National Institute of Standards and Technology (United States)

P-18: CNN to mitigate atmospheric turbulence effect on Shack-Hartmann Wavefront Sensing: A case study on the Magdalena Ridge Observatory Interferometer., Siavash Norouzi1, James J. Luis2, Ramyaa Ramyaa1, John S. Young2, Eugene B. Seneta2, Morteza Darvish Morshedi Hosseini3, Edgar R. Ligon4; 1New Mexico Institute of Mining and Technology, Socorro, NM, United States; 2University of Cambridge, Cambridge, United Kingdom; 3Binghamton University, Binghamton, NY, United States; 4CHARA Array, Mt. Wilson, CA, United States.

P-19: ISP distillation, Eli Schwartz1, Alex Bronstein2, Raja Giryes1; 1Tel Aviv University, Atlit, Israel; 2Technion, Haifa, Israel.

Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications 2022

P-22: Chatbot integrated with machine learning deployed in the cloud and performance evaluation, Ganesh Reddy Gunnam1, Rahul Mundlamuri1, Devasena Inupakutika1, Sahak Kaghyan1, David Akopian1; 1The University of Texas at San Antonio, San Antonio, TX, United States.

P-23: Chatbot integration with Google Dialogflow environment, Rahul Mundlamuri1, Devasena Inupakutika1, David Akopian1, Ganesh Reddy Gunnam1, Sahak Kaghyan1; 1The University of Texas at San Antonio, San Antonio, TX, United States.

P-24: Interactive books - Status report, Harvey R. Levenson1; 1Cal Poly, San Luis Obispo, CA, United States.

Media Watermarking, Security, and Forensics 2022

P-23: Robust face recognition: How much face is needed?, Niklas Bunzel1; 1Fraunhofer Institute for Secure Information Technology, Darmstadt, Germany.

P-24: Using a GAN to generate adversarial examples to facial image recognition, Andrew Merrigan1, Alan Smeaton1; 1Dublin City University, Dublin, Ireland.

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