NTIRE 2019 challenge on video deblurring: Methods and results

Seungjun Nah; Radu Timofte; Sungyong Baik; Seokil Hong; Gyeongsik Moon; Sanghyun Son; Kyoung Mu Lee; Xintao Wang; Kelvin C.K. Chan; Ke Yu; Chao Dong; Chen Change Loy; Yuchen Fan; Jiahui Yu; DIng Liu; Thomas S. Huang; Hyeonjun Sim; Munchurl Kim; Dongwon Park; Jisoo Kim; Se Young Chun; Muhammad Haris; Greg Shakhnarovich; Norimichi Ukita; Syed Waqas Zamir; Aditya Arora; Salman Khan; Fahad Shahbaz Khan; Ling Shao; Rahul Kumar Gupta; Vishal Chudasama; Heena Patel; Kishor Upla; Hongfei Fan; Guo Li; Yumei Zhang; Xiang Li; Wenjie Zhang; Qingwen He; Kuldeep Purohit; A. N. Rajagopalan; Jeonghun Kim; Mohammad Tofighi; Tiantong Guo; Vishal Monga

doi:10.1109/CVPRW.2019.00249

NTIRE 2019 challenge on video deblurring: Methods and results

Seungjun Nah, Radu Timofte, Sungyong Baik, Seokil Hong, Gyeongsik Moon, Sanghyun Son, Kyoung Mu Lee, Xintao Wang, Kelvin C.K. Chan, Ke Yu, Chao Dong, Chen Change Loy, Yuchen Fan, Jiahui Yu, DIng Liu, Thomas S. Huang, Hyeonjun Sim, Munchurl Kim, Dongwon Park, Jisoo KimSe Young Chun, Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita, Syed Waqas Zamir, Aditya Arora, Salman Khan, Fahad Shahbaz Khan, Ling Shao, Rahul Kumar Gupta, Vishal Chudasama, Heena Patel, Kishor Upla, Hongfei Fan, Guo Li, Yumei Zhang, Xiang Li, Wenjie Zhang, Qingwen He, Kuldeep Purohit, A. N. Rajagopalan, Jeonghun Kim, Mohammad Tofighi, Tiantong Guo, Vishal Monga

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

30 Citations (Scopus)

Abstract

This paper reviews the first NTIRE challenge on video deblurring (restoration of rich details and high frequency components from blurred video frames) with focus on the proposed solutions and results. A new REalistic and Diverse Scenes dataset (REDS) was employed. The challenge was divided into 2 tracks. Track 1 employed dynamic motion blurs while Track 2 had additional MPEG video compression artifacts. Each competition had 109 and 93 registered participants. Total 13 teams competed in the final testing phase. They gauge the state-of-the-art in video deblurring problem.

Original language	English
Title of host publication	Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019
Publisher	IEEE Computer Society
Pages	1974-1984
Number of pages	11
ISBN (Electronic)	9781728125060
DOIs	https://doi.org/10.1109/CVPRW.2019.00249
Publication status	Published - Jun 2019
Externally published	Yes
Event	32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019 - Long Beach, United States Duration: Jun 16 2019 → Jun 20 2019

Publication series

Name	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume	2019-June
ISSN (Print)	2160-7508
ISSN (Electronic)	2160-7516

Conference

Conference	32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019
Country/Territory	United States
City	Long Beach
Period	6/16/19 → 6/20/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

ASJC Scopus Subject Areas

Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

Access to Document

10.1109/CVPRW.2019.00249

Cite this

Nah, S., Timofte, R., Baik, S., Hong, S., Moon, G., Son, S., Lee, K. M., Wang, X., Chan, K. C. K., Yu, K., Dong, C., Loy, C. C., Fan, Y., Yu, J., Liu, DI., Huang, T. S., Sim, H., Kim, M., Park, D., ... Monga, V. (2019). NTIRE 2019 challenge on video deblurring: Methods and results. In Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019 (pp. 1974-1984). Article 9025548 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2019-June). IEEE Computer Society. https://doi.org/10.1109/CVPRW.2019.00249

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title = "NTIRE 2019 challenge on video deblurring: Methods and results",

abstract = "This paper reviews the first NTIRE challenge on video deblurring (restoration of rich details and high frequency components from blurred video frames) with focus on the proposed solutions and results. A new REalistic and Diverse Scenes dataset (REDS) was employed. The challenge was divided into 2 tracks. Track 1 employed dynamic motion blurs while Track 2 had additional MPEG video compression artifacts. Each competition had 109 and 93 registered participants. Total 13 teams competed in the final testing phase. They gauge the state-of-the-art in video deblurring problem.",

author = "Seungjun Nah and Radu Timofte and Sungyong Baik and Seokil Hong and Gyeongsik Moon and Sanghyun Son and Lee, \{Kyoung Mu\} and Xintao Wang and Chan, \{Kelvin C.K.\} and Ke Yu and Chao Dong and Loy, \{Chen Change\} and Yuchen Fan and Jiahui Yu and DIng Liu and Huang, \{Thomas S.\} and Hyeonjun Sim and Munchurl Kim and Dongwon Park and Jisoo Kim and Chun, \{Se Young\} and Muhammad Haris and Greg Shakhnarovich and Norimichi Ukita and Zamir, \{Syed Waqas\} and Aditya Arora and Salman Khan and Khan, \{Fahad Shahbaz\} and Ling Shao and Gupta, \{Rahul Kumar\} and Vishal Chudasama and Heena Patel and Kishor Upla and Hongfei Fan and Guo Li and Yumei Zhang and Xiang Li and Wenjie Zhang and Qingwen He and Kuldeep Purohit and Rajagopalan, \{A. N.\} and Jeonghun Kim and Mohammad Tofighi and Tiantong Guo and Vishal Monga",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019 ; Conference date: 16-06-2019 Through 20-06-2019",

year = "2019",

month = jun,

doi = "10.1109/CVPRW.2019.00249",

language = "English",

series = "IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops",

publisher = "IEEE Computer Society",

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booktitle = "Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019",

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Nah, S, Timofte, R, Baik, S, Hong, S, Moon, G, Son, S, Lee, KM, Wang, X, Chan, KCK, Yu, K, Dong, C, Loy, CC, Fan, Y, Yu, J, Liu, DI, Huang, TS, Sim, H, Kim, M, Park, D, Kim, J, Chun, SY, Haris, M, Shakhnarovich, G, Ukita, N, Zamir, SW, Arora, A, Khan, S, Khan, FS, Shao, L, Gupta, RK, Chudasama, V, Patel, H, Upla, K, Fan, H, Li, G, Zhang, Y, Li, X, Zhang, W, He, Q, Purohit, K, Rajagopalan, AN, Kim, J, Tofighi, M, Guo, T & Monga, V 2019, NTIRE 2019 challenge on video deblurring: Methods and results. in Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019., 9025548, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, vol. 2019-June, IEEE Computer Society, pp. 1974-1984, 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019, Long Beach, United States, 6/16/19. https://doi.org/10.1109/CVPRW.2019.00249

NTIRE 2019 challenge on video deblurring: Methods and results. / Nah, Seungjun; Timofte, Radu; Baik, Sungyong et al.
Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019. IEEE Computer Society, 2019. p. 1974-1984 9025548 (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops; Vol. 2019-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

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AU - Nah, Seungjun

AU - Timofte, Radu

AU - Baik, Sungyong

AU - Hong, Seokil

AU - Moon, Gyeongsik

AU - Son, Sanghyun

AU - Lee, Kyoung Mu

AU - Wang, Xintao

AU - Chan, Kelvin C.K.

AU - Yu, Ke

AU - Dong, Chao

AU - Loy, Chen Change

AU - Fan, Yuchen

AU - Yu, Jiahui

AU - Liu, DIng

AU - Huang, Thomas S.

AU - Sim, Hyeonjun

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AU - Park, Dongwon

AU - Kim, Jisoo

AU - Chun, Se Young

AU - Haris, Muhammad

AU - Shakhnarovich, Greg

AU - Ukita, Norimichi

AU - Zamir, Syed Waqas

AU - Arora, Aditya

AU - Khan, Salman

AU - Khan, Fahad Shahbaz

AU - Shao, Ling

AU - Gupta, Rahul Kumar

AU - Chudasama, Vishal

AU - Patel, Heena

AU - Upla, Kishor

AU - Fan, Hongfei

AU - Li, Guo

AU - Zhang, Yumei

AU - Li, Xiang

AU - Zhang, Wenjie

AU - He, Qingwen

AU - Purohit, Kuldeep

AU - Rajagopalan, A. N.

AU - Kim, Jeonghun

AU - Tofighi, Mohammad

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AB - This paper reviews the first NTIRE challenge on video deblurring (restoration of rich details and high frequency components from blurred video frames) with focus on the proposed solutions and results. A new REalistic and Diverse Scenes dataset (REDS) was employed. The challenge was divided into 2 tracks. Track 1 employed dynamic motion blurs while Track 2 had additional MPEG video compression artifacts. Each competition had 109 and 93 registered participants. Total 13 teams competed in the final testing phase. They gauge the state-of-the-art in video deblurring problem.

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M3 - Conference contribution

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T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

SP - 1974

EP - 1984

BT - Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019

PB - IEEE Computer Society

Y2 - 16 June 2019 through 20 June 2019

ER -

Nah S, Timofte R, Baik S, Hong S, Moon G, Son S et al. NTIRE 2019 challenge on video deblurring: Methods and results. In Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019. IEEE Computer Society. 2019. p. 1974-1984. 9025548. (IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops). doi: 10.1109/CVPRW.2019.00249

NTIRE 2019 challenge on video deblurring: Methods and results

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus Subject Areas

Access to Document

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