Abstract
The rising demand for computational photography on mobile devices drives development of advanced image sensors and algorithms for camera systems. But the lack of opportunities for in-depth exchange between industry and academia are constraining the development of Mobile Intelligent Photography and Imaging (MIPI). Building on the successes of the prior MIPI Workshops at ECCV 2022 and CVPR 2023, we are pleased to introduce our third MIPI challenge, which includes three tracks focusing on novel image sensors and imaging algorithms. In this paper, we summarize and review the Demosaic for Hybridevs Camera track on MIPI 2024. A total of 110 participants from both industrial and academic backgrounds contributed many valuable solutions to address the difficulty of the restoration of HybridEVS's raw data, thus raising the reconstructed performance to a new height. This paper gives a comprehensive description and analysis of all solutions developed during this challenge. More detailed information about this challenge is available at https://mipi-challenge.org/MIPI2024.
Original language | English |
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Title of host publication | Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024 |
Publisher | IEEE Computer Society |
Pages | 1136-1143 |
Number of pages | 8 |
ISBN (Electronic) | 9798350365474 |
DOIs | |
Publication status | Published - 2024 |
Externally published | Yes |
Event | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024 - Seattle, United States Duration: Jun 16 2024 → Jun 22 2024 |
Publication series
Name | IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops |
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ISSN (Print) | 2160-7508 |
ISSN (Electronic) | 2160-7516 |
Conference
Conference | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024 |
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Country/Territory | United States |
City | Seattle |
Period | 6/16/24 → 6/22/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
ASJC Scopus Subject Areas
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
Keywords
- computational photography
- demosaicking
- hybridEVS