ICCP 2021 : IEEE International Conference on Computational Photography
in Conferences Posted on October 30, 2020Conference Information
Submission Deadline | Friday 11 Dec 2020 |
Proceedings indexed by : ![]() |
Conference Dates | May 23, 2021 - May 25, 2021 | |
Conference Address |
Technion, Israel ![]() |
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Conference & Submission Link | https://iccp-conference.org/ |

Conference Ranking & Metrics (This is a TOP Conference)
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Proceedings | https://ieeexplore.ieee.org/xpl/conhome/1800125/all-proceedings |
DBLP Page | https://dblp.uni-trier.de/db/conf/iccp |
Conference Call for Papers
We call for you to submit your work on computational photography to the IEEE International Conference on Computational Photography (ICCP 2021). We seek works of the highest significance, interest and potential for impact. Concepts, problems, methods and results which are creative, daring, novel and thought-provoking are particularly appreciated. ICCP’2021 prioritizes interesting ideas over perfect increments. Journal-quality paper submissions (of entirely novel work) are welcome: we are currently working to formulate a process with a major IEEE journal, similarly to ICCP’2020 (details soon).
Computational photography is a vibrant area at the intersection of imaging, sensors, signal processing, computer vision and graphics. It seeks the creation of new photographic and imaging functionalities and experiences that go beyond the possibilities of exclusive, disparate camera and image processing technologies. This cross-disciplinary field further seeks a better understanding of imaging models, perception and limits, through holistic analysis.
We welcome high quality submissions including, but not limited to, those in the following areas:
Computational image acquisition, e.g. coded apertures
Computational illumination and displays
Advanced Image and video processing
Computational optics, e.g., wavefront coding, digital holography
Imaging by compressive sensing
Scientific imaging (e.g, microscopy, astronomy, biomed, geophysics)
Integration of image sensing with machine learning
Hardware for imaging sensors and illumination
Organizing and exploiting photo/video data
Capture of appearance, shape, illumination and underlying physical properties
Imaging, display and Illumination for user interfaces, e.g., AR/VR
Imaging models and limits
Physics-based rendering
Mobile Imagin
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