TY - GEN
T1 - Thermal Image Super-Resolution Challenge Results - PBVS 2024
AU - Rivadeneira, Rafael E.
AU - Sappa, Angel D.
AU - Wang, Chenyang
AU - Zhong, Zhiwei
AU - Jiang, Junjun
AU - Kim, Jin
AU - Kang, Dongyeon
AU - Kim, Dogun
AU - Zhou, Weiwei
AU - Ling, Chengkun
AU - Lu, Jiada
AU - Chen, Peilin
AU - Wang, Shiqi
AU - Gwon, Huiwon
AU - Jo, Hyejeong
AU - Jo, Sunhee
AU - Yoon, Jiseok
AU - Jang, Wonseok
AU - Song, Haseok
AU - Puttagunta, Raghunath Sai
AU - Li, Zhu
AU - York, George
AU - Arnold, Cyprien
AU - Seoud, Lama
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper outlines the advancements and results of the Fifth Thermal Image Super-Resolution challenge, hosted at the Perception Beyond the Visible Spectrum CVPR 2024 workshop. The challenge employed a novel benchmark cross-spectral dataset consisting of 1000 thermal images, each paired with its corresponding registered RGB image. The challenge featured two tracks: Track-1 focused on Single Thermal Image Super-Resolution with an ×8 upscale factor, while Track-2 extended its evaluation to include both ×8 and ×16 scaling factors, utilizing high-resolution RGB images to guide the super-resolution process for low-resolution thermal images. The participation of over 175 teams highlights the research community's strong engagement and dedication to enhancing image resolution techniques across both single and cross-spectral methodologies. This year's challenge sets new benchmarks and provides valuable insights into future directions for research in thermal image super-resolution.
AB - This paper outlines the advancements and results of the Fifth Thermal Image Super-Resolution challenge, hosted at the Perception Beyond the Visible Spectrum CVPR 2024 workshop. The challenge employed a novel benchmark cross-spectral dataset consisting of 1000 thermal images, each paired with its corresponding registered RGB image. The challenge featured two tracks: Track-1 focused on Single Thermal Image Super-Resolution with an ×8 upscale factor, while Track-2 extended its evaluation to include both ×8 and ×16 scaling factors, utilizing high-resolution RGB images to guide the super-resolution process for low-resolution thermal images. The participation of over 175 teams highlights the research community's strong engagement and dedication to enhancing image resolution techniques across both single and cross-spectral methodologies. This year's challenge sets new benchmarks and provides valuable insights into future directions for research in thermal image super-resolution.
UR - https://www.scopus.com/pages/publications/85201463802
U2 - 10.1109/CVPRW63382.2024.00317
DO - 10.1109/CVPRW63382.2024.00317
M3 - 会议稿件
AN - SCOPUS:85201463802
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 3113
EP - 3122
BT - Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024
PB - IEEE Computer Society
T2 - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024
Y2 - 16 June 2024 through 22 June 2024
ER -