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Extract from the Register of European Patents

EP About this file: EP4004875

EP4004875 - CROSS-MODALITY IMAGE GENERATION [Right-click to bookmark this link]
StatusExamination is in progress
Status updated on  24.11.2023
Database last updated on 16.11.2024
FormerRequest for examination was made
Status updated on  29.04.2022
FormerThe international publication has been made
Status updated on  29.01.2021
Formerunknown
Status updated on  21.08.2020
Most recent event   Tooltip05.09.2024New entry: Additional fee for renewal fee: despatch of communication + time limit 
Applicant(s)For all designated states
Raytheon Company
870 Winter Street
Waltham, Massachusetts 02451-1449 / US
[2022/22]
Inventor(s)01 / BONGIO KARRMAN, Anton
12540 Braddock Dr. 207
Los Angeles, California 90066 / US
02 / FAN, Ryan C.
417 S. Hill St. 1101
Los Angeles, California 90013 / US
 [2022/22]
Representative(s)Dentons UK and Middle East LLP
One Fleet Place
London EC4M 7WS / GB
[2022/22]
Application number, filing date20754469.322.07.2020
[2022/22]
WO2020US43085
Priority number, dateUS201962877167P22.07.2019         Original published format: US 201962877167 P
US201962877182P22.07.2019         Original published format: US 201962877182 P
[2022/22]
Filing languageEN
Procedural languageEN
PublicationType: A1 Application with search report
No.:WO2021016358
Date:28.01.2021
Language:EN
[2021/04]
Type: A1 Application with search report 
No.:EP4004875
Date:01.06.2022
Language:EN
The application published by WIPO in one of the EPO official languages on 28.01.2021 takes the place of the publication of the European patent application.
[2022/22]
Search report(s)International search report - published on:EP28.01.2021
ClassificationIPC:G06T11/00, G06T7/50, G06T7/38
[2022/22]
CPC:
G06T7/30 (EP,US); G06T3/14 (US); G01S13/90 (US);
G06N20/00 (US); G06N20/20 (US); G06T7/50 (US);
G06T7/74 (US); G06T2207/10004 (EP); G06T2207/10028 (EP);
G06T2207/10044 (EP,US); G06T2207/10072 (US); G06T2207/20076 (US);
G06T2207/20081 (EP,US); G06T2207/20084 (EP); G06T2207/20224 (US);
G06T2207/30181 (EP); G06T2207/30244 (US) (-)
Designated contracting statesAL,   AT,   BE,   BG,   CH,   CY,   CZ,   DE,   DK,   EE,   ES,   FI,   FR,   GB,   GR,   HR,   HU,   IE,   IS,   IT,   LI,   LT,   LU,   LV,   MC,   MK,   MT,   NL,   NO,   PL,   PT,   RO,   RS,   SE,   SI,   SK,   SM,   TR [2022/22]
TitleGerman:MODALITÄTSÜBERGREIFENDE BILDERZEUGUNG[2022/22]
English:CROSS-MODALITY IMAGE GENERATION[2022/22]
French:GÉNÉRATION D'IMAGES À MODALITÉS CROISÉES[2022/22]
Entry into regional phase22.02.2022National basic fee paid 
22.02.2022Designation fee(s) paid 
22.02.2022Examination fee paid 
Examination procedure22.02.2022Amendment by applicant (claims and/or description)
22.02.2022Examination requested  [2022/22]
22.02.2022Date on which the examining division has become responsible
24.11.2023Despatch of a communication from the examining division (Time limit: M04)
06.02.2024Reply to a communication from the examining division
Fees paidRenewal fee
21.07.2022Renewal fee patent year 03
20.07.2023Renewal fee patent year 04
Penalty fee
Additional fee for renewal fee
31.07.202405   M06   Not yet paid
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See the Register of the Unified Patent Court for opt-out data
Responsibility for the accuracy, completeness or quality of the data displayed under the link provided lies entirely with the Unified Patent Court.
Cited inInternational search[XAI]  - Namil Kim ET AL, "Multispectral Transfer Network: Unsupervised Depth Estimation for All-Day Vision", AAAI Conference on Artificial Intelligence, North America, (20180401), pages 6983 - 6991, URL: https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16771/16286, (20201019), XP055741389 [X] 1,3-5,8,10-12,15,17-19 * sections Multispectral Stereo Dataset, Efficient Multi-task Learning, Unsupervised Depth Estimation, Training Loss; page 6984 - page 6986; figures 2,3,8 * [A] 2,9,16 [I] 6,7,13,14,20
 [A]  - ZHOU TINGHUI ET AL, "Unsupervised Learning of Depth and Ego-Motion from Video", 2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), IEEE COMPUTER SOCIETY, US, doi:10.1109/CVPR.2017.700, ISSN 1063-6919, (20170721), pages 6612 - 6619, (20171106), XP033250026 [A] 1-20 * abstract *

DOI:   http://dx.doi.org/10.1109/CVPR.2017.700
 [A]  - Matthias Limmer ET AL, "Infrared Colorization Using Deep Convolutional Neural Networks", doi:10.1109/ICMLA.2016.0019, (20160408), URL: https://arxiv.org/pdf/1604.02245.pdf, XP055434299 [A] 1-20 * abstract *

DOI:   http://dx.doi.org/10.1109/ICMLA.2016.0019
 [A]  - QAYYNM USMAN ET AL, "Thermal colorization using deep neural network", 2018 15TH INTERNATIONAL BHURBAN CONFERENCE ON APPLIED SCIENCES AND TECHNOLOGY (IBCAST), IEEE, (20180109), doi:10.1109/IBCAST.2018.8312243, pages 325 - 329, XP033329143 [A] 1-20 * abstract *

DOI:   http://dx.doi.org/10.1109/IBCAST.2018.8312243
The EPO accepts no responsibility for the accuracy of data originating from other authorities; in particular, it does not guarantee that it is complete, up to date or fit for specific purposes.