{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T16:56:01Z","timestamp":1777568161347,"version":"3.51.4"},"publisher-location":"Cham","reference-count":87,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031250651","type":"print"},{"value":"9783031250668","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-25066-8_5","type":"book-chapter","created":{"date-parts":[[2023,2,17]],"date-time":"2023-02-17T08:18:05Z","timestamp":1676621885000},"page":"92-129","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Efficient and\u00a0Accurate Quantized Image Super-Resolution on\u00a0Mobile NPUs, Mobile AI & AIM 2022 Challenge: Report"],"prefix":"10.1007","author":[{"given":"Andrey","family":"Ignatov","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Radu","family":"Timofte","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maurizio","family":"Denna","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdel","family":"Younes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ganzorig","family":"Gankhuyag","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingang","family":"Huh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Myeong Kyun","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kihwan","family":"Yoon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyeon-Cheol","family":"Moon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seungho","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yoonsik","family":"Choe","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinwoo","family":"Jeong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sungjei","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maciej","family":"Smyl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tomasz","family":"Latkowski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pawel","family":"Kubik","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michal","family":"Sokolski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujie","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahao","family":"Chao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhou","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongfan","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengfeng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenbing","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengyang","family":"Zhuge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenghua","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengdi","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ran","family":"Duan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lingshun","family":"Kong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingdong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiawei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaqi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinshan","family":"Pan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gaocheng","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhe","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongbin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hojin","family":"Cho","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steve","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huaen","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanbo","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziwei","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Youwei","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihong","family":"Wen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoqiang","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuaicheng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lize","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhikai","family":"Zong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeremy","family":"Kwon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junxi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengyuan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nianxiang","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanchen","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Han","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenzhong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gen","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanfan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dafeng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neo","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fitz","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jerry","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mustafa","family":"Ayazoglu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bahri Batuhan","family":"Bilecen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shota","family":"Hirose","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kasidis","family":"Arunruangsirilert","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luo","family":"Ao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ho Chun","family":"Leung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrew","family":"Wei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dahai","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Luo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ce","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seongmin","family":"Hong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongwon","family":"Park","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joonhee","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Byeong Hyun","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seunggyu","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Se Young","family":"Chun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruiyuan","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuhao","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haihang","family":"Ruan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinjian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Garas","family":"Gendy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nabil","family":"Sabor","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingchao","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanghui","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,2,18]]},"reference":[{"key":"5_CR1","unstructured":"Abdelhamed, A., Afifi, M., Timofte, R., Brown, M.S.: Ntire 2020 challenge on real image denoising: dataset, methods and results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 496\u2013497 (2020)"},{"key":"5_CR2","unstructured":"Abdelhamed, A., Timofte, R., Brown, M.S.: Ntire 2019 challenge on real image denoising: Methods and results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2019)"},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"Agustsson, E., Timofte, R.: Ntire 2017 challenge on single image super-resolution: dataset and study. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 126\u2013135 (2017)","DOI":"10.1109\/CVPRW.2017.150"},{"issue":"3","key":"5_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3005348","volume":"13","author":"S Anwar","year":"2017","unstructured":"Anwar, S., Hwang, K., Sung, W.: Structured pruning of deep convolutional neural networks. ACM J. Emerg. Technol. Comput. Syst. (JETC) 13(3), 1\u201318 (2017)","journal-title":"ACM J. Emerg. Technol. Comput. Syst. (JETC)"},{"key":"5_CR5","unstructured":"Anwar, S., Sung, W.: Compact deep convolutional neural networks with coarse pruning. arXiv preprint arXiv:1610.09639 (2016)"},{"key":"5_CR6","doi-asserted-by":"crossref","unstructured":"Ayazoglu, M.: Extremely lightweight quantization robust real-time single-image super resolution for mobile devices. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2021)","DOI":"10.1109\/CVPRW53098.2021.00280"},{"key":"5_CR7","doi-asserted-by":"crossref","unstructured":"Ayazoglu, M., Bilecen, B.B.: XCAT - lightweight quantized single image super-resolution using heterogeneous group convolutions and cross concatenation. In: Proceedings of the European Conference on Computer Vision (ECCV) Workshops (2022)","DOI":"10.1007\/978-3-031-25063-7_29"},{"key":"5_CR8","first-page":"529","volume":"4","author":"K Bhardwaj","year":"2022","unstructured":"Bhardwaj, K., et al.: Collapsible linear blocks for super-efficient super resolution. Proc. Mach. Learn. Syst. 4, 529\u2013547 (2022)","journal-title":"Proc. Mach. Learn. Syst."},{"key":"5_CR9","unstructured":"Cai, J., Gu, S., Timofte, R., Zhang, L.: Ntire 2019 challenge on real image super-resolution: methods and results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2019)"},{"key":"5_CR10","doi-asserted-by":"crossref","unstructured":"Cai, Y., Yao, Z., Dong, Z., Gholami, A., Mahoney, M.W., Keutzer, K.: Zeroq: A novel zero shot quantization framework. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13169\u201313178 (2020)","DOI":"10.1109\/CVPR42600.2020.01318"},{"key":"5_CR11","doi-asserted-by":"crossref","unstructured":"Chiang, C.M., et al.: Deploying image deblurring across mobile devices: a perspective of quality and latency. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 502\u2013503 (2020)","DOI":"10.1109\/CVPRW50498.2020.00259"},{"key":"5_CR12","unstructured":"Conde, M.V., Timofte, R., et al.: Reversed image signal processing and RAW reconstruction. AIM 2022 Challenge Report. In: Proceedings of the European Conference on Computer Vision (ECCV) Workshops (2022)"},{"key":"5_CR13","doi-asserted-by":"crossref","unstructured":"Ding, X., Zhang, X., Han, J., Ding, G.: Diverse branch block: Building a convolution as an inception-like unit. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10886\u201310895 (2021)","DOI":"10.1109\/CVPR46437.2021.01074"},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Ding, X., Zhang, X., Ma, N., Han, J., Ding, G., Sun, J.: RepVGG: making VGG-style convnets great again. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13733\u201313742 (2021)","DOI":"10.1109\/CVPR46437.2021.01352"},{"key":"5_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1007\/978-3-319-10593-2_13","volume-title":"Computer Vision \u2013 ECCV 2014","author":"C Dong","year":"2014","unstructured":"Dong, C., Loy, C.C., He, K., Tang, X.: Learning a deep convolutional network for image super-resolution. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8692, pp. 184\u2013199. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10593-2_13"},{"issue":"2","key":"5_CR16","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1109\/TPAMI.2015.2439281","volume":"38","author":"C Dong","year":"2015","unstructured":"Dong, C., Loy, C.C., He, K., Tang, X.: Image super-resolution using deep convolutional networks. IEEE Trans. Pattern Anal. Mach. Intell. 38(2), 295\u2013307 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"5_CR17","unstructured":"Dozat, T.: Incorporating nesterov momentum into Adam (2016)"},{"key":"5_CR18","doi-asserted-by":"crossref","unstructured":"Du, Z., Liu, D., Liu, J., Tang, J., Wu, G., Fu, L.: Fast and memory-efficient network towards efficient image super-resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 853\u2013862 (2022)","DOI":"10.1109\/CVPRW56347.2022.00101"},{"key":"5_CR19","doi-asserted-by":"crossref","unstructured":"Du, Z., Liu, J., Tang, J., Wu, G.: Anchor-based plain net for mobile image super-resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2021)","DOI":"10.1109\/CVPRW53098.2021.00283"},{"issue":"2","key":"5_CR20","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/38.988747","volume":"22","author":"WT Freeman","year":"2002","unstructured":"Freeman, W.T., Jones, T.R., Pasztor, E.C.: Example-based super-resolution. IEEE Comput. Graphics Appl. 22(2), 56\u201365 (2002)","journal-title":"IEEE Comput. Graphics Appl."},{"key":"5_CR21","doi-asserted-by":"crossref","unstructured":"Gendy, G., nabil sabor, Hou, J., He, G.: Real-time channel mixing net for mobile image super-resolution. In: Proceedings of the European Conference on Computer Vision (ECCV) Workshops (2022)","DOI":"10.1007\/978-3-031-25063-7_36"},{"key":"5_CR22","doi-asserted-by":"crossref","unstructured":"Howard, A., et al.: Searching for mobilenetv3. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1314\u20131324 (2019)","DOI":"10.1109\/ICCV.2019.00140"},{"key":"5_CR23","doi-asserted-by":"crossref","unstructured":"Huang, J.B., Singh, A., Ahuja, N.: Single image super-resolution from transformed self-exemplars. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5197\u20135206 (2015)","DOI":"10.1109\/CVPR.2015.7299156"},{"key":"5_CR24","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Byeoung-su, K., Timofte, R.: Fast camera image denoising on mobile GPUs with deep learning, mobile AI 2021 challenge: Report. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2021)","DOI":"10.1109\/CVPRW53098.2021.00285"},{"key":"5_CR25","unstructured":"Ignatov, A., Chiang, J., Kuo, H.K., Sycheva, A., Timofte, R.: Learned smartphone ISP on mobile NPUs with deep learning, mobile AI 2021 challenge: report. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2021)"},{"key":"5_CR26","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Kobyshev, N., Timofte, R., Vanhoey, K., Van Gool, L.: DSLR-quality photos on mobile devices with deep convolutional networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3277\u20133285 (2017)","DOI":"10.1109\/ICCV.2017.355"},{"key":"5_CR27","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Kobyshev, N., Timofte, R., Vanhoey, K., Van Gool, L.: WESPE: weakly supervised photo enhancer for digital cameras. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshop, pp. 691\u2013700 (2018)","DOI":"10.1109\/CVPRW.2018.00112"},{"key":"5_CR28","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Malivenko, G., Plowman, D., Shukla, S., Timofte, R.: Fast and accurate single-image depth estimation on mobile devices, mobile AI 2021 challenge: report. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2021)","DOI":"10.1109\/CVPRW53098.2021.00288"},{"key":"5_CR29","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Malivenko, G., Timofte, R.: Fast and accurate quantized camera scene detection on smartphones, mobile AI 2021 challenge: report. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2021)","DOI":"10.1109\/CVPRW53098.2021.00289"},{"key":"5_CR30","doi-asserted-by":"crossref","unstructured":"Ignatov, A., et al.: PyNet-V2 mobile: efficient on-device photo processing with neural networks. In: 2021 26th International Conference on Pattern Recognition (ICPR). IEEE (2022)","DOI":"10.1109\/ICPR56361.2022.9956598"},{"key":"5_CR31","unstructured":"Ignatov, A., Malivenko, G., Timofte, R., et al.: Efficient single-image depth estimation on mobile devices, mobile AI & aim 2022 challenge: Report. In: European Conference on Computer Vision (2022)"},{"key":"5_CR32","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Patel, J., Timofte, R.: Rendering natural camera bokeh effect with deep learning. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 418\u2013419 (2020)","DOI":"10.1109\/CVPRW50498.2020.00217"},{"key":"5_CR33","doi-asserted-by":"crossref","unstructured":"Ignatov, A., et al.: Aim 2019 challenge on bokeh effect synthesis: Methods and results. In: 2019 IEEE\/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 3591\u20133598. IEEE (2019)","DOI":"10.1109\/ICCVW.2019.00444"},{"key":"5_CR34","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Romero, A., Kim, H., Timofte, R.: Real-time video super-resolution on smartphones with deep learning, mobile AI 2021 challenge: report. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2021)","DOI":"10.1109\/CVPRW53098.2021.00287"},{"key":"5_CR35","doi-asserted-by":"crossref","unstructured":"Ignatov, A., et al.: MicroISP: processing 32mp photos on mobile devices with deep learning. In: European Conference on Computer Vision (2022)","DOI":"10.1007\/978-3-031-25063-7_46"},{"key":"5_CR36","unstructured":"Ignatov, A., Timofte, R.: Ntire 2019 challenge on image enhancement: methods and results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2019)"},{"key":"5_CR37","doi-asserted-by":"crossref","unstructured":"Ignatov, A., et al.: Power efficient video super-resolution on mobile NPUs with deep learning, mobile AI & aim 2022 challenge: report. In: European Conference on Computer Vision (2022)","DOI":"10.1109\/CVPRW53098.2021.00286"},{"key":"5_CR38","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"288","DOI":"10.1007\/978-3-030-11021-5_19","volume-title":"Computer Vision \u2013 ECCV 2018 Workshops","author":"A Ignatov","year":"2019","unstructured":"Ignatov, A., et al.: AI benchmark: running deep neural networks on android smartphones. In: Leal-Taix\u00e9, L., Roth, S. (eds.) ECCV 2018. LNCS, vol. 11133, pp. 288\u2013314. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11021-5_19"},{"key":"5_CR39","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Timofte, R., Denna, M., Younes, A.: Real-time quantized image super-resolution on mobile NPUs, mobile AI 2021 challenge: report. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (2021)","DOI":"10.1109\/CVPRW53098.2021.00286"},{"key":"5_CR40","doi-asserted-by":"crossref","unstructured":"Ignatov, A., et al.: Aim 2019 challenge on raw to RGB mapping: methods and results. In: 2019 IEEE\/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 3584\u20133590. IEEE (2019)","DOI":"10.1109\/ICCVW.2019.00443"},{"key":"5_CR41","doi-asserted-by":"crossref","unstructured":"Ignatov, A., et al.: Ai benchmark: all about deep learning on smartphones in 2019. In: 2019 IEEE\/CVF International Conference on Computer Vision Workshop (ICCVW), pp. 3617\u20133635. IEEE (2019)","DOI":"10.1109\/ICCVW.2019.00447"},{"key":"5_CR42","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1007\/978-3-030-67070-2_13","volume-title":"Computer Vision \u2013 ECCV 2020 Workshops","author":"A Ignatov","year":"2020","unstructured":"Ignatov, A., et al.: AIM 2020 challenge on rendering realistic Bokeh. In: Bartoli, A., Fusiello, A. (eds.) ECCV 2020. LNCS, vol. 12537, pp. 213\u2013228. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-67070-2_13"},{"key":"5_CR43","unstructured":"Ignatov, A., et al.: Pirm challenge on perceptual image enhancement on smartphones: Report. In: Proceedings of the European Conference on Computer Vision (ECCV) Workshops (2018)"},{"key":"5_CR44","unstructured":"Ignatov, A., et al.: Aim 2020 challenge on learned image signal processing pipeline. arXiv preprint arXiv:2011.04994 (2020)"},{"key":"5_CR45","unstructured":"Ignatov, A., Timofte, R., et al.: Learned smartphone ISP on mobile GPUs with deep learning, mobile AI & aim 2022 challenge: report. In: European Conference on Computer Vision (2022)"},{"key":"5_CR46","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Timofte, R., et al.: Realistic bokeh effect rendering on mobile GPUs, mobile AI & aim 2022 challenge: report (2022)","DOI":"10.1007\/978-3-031-25066-8_7"},{"key":"5_CR47","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Van Gool, L., Timofte, R.: Replacing mobile camera ISP with a single deep learning model. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 536\u2013537 (2020)","DOI":"10.1109\/CVPRW50498.2020.00276"},{"key":"5_CR48","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1016\/j.patrec.2020.07.033","volume":"138","author":"D Ignatov","year":"2020","unstructured":"Ignatov, D., Ignatov, A.: Controlling information capacity of binary neural network. Pattern Recogn. Lett. 138, 276\u2013281 (2020)","journal-title":"Pattern Recogn. Lett."},{"key":"5_CR49","unstructured":"Inc., S.: https:\/\/www.synaptics.com\/technology\/edge-computing"},{"key":"5_CR50","doi-asserted-by":"crossref","unstructured":"Irani, M., Peleg, S.: Improving resolution by image registration. CVGIP: Graph. Models Image Process. 53(3), 231\u2013239 (1991)","DOI":"10.1016\/1049-9652(91)90045-L"},{"key":"5_CR51","doi-asserted-by":"crossref","unstructured":"Jacob, B., et al.: Quantization and training of neural networks for efficient integer-arithmetic-only inference. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2704\u20132713 (2018)","DOI":"10.1109\/CVPR.2018.00286"},{"key":"5_CR52","unstructured":"Jain, S.R., Gural, A., Wu, M., Dick, C.H.: Trained quantization thresholds for accurate and efficient fixed-point inference of deep neural networks. arXiv preprint arXiv:1903.08066 (2019)"},{"key":"5_CR53","doi-asserted-by":"crossref","unstructured":"Kim, J., Lee, J.K., Lee, K.M.: Accurate image super-resolution using very deep convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1646\u20131654 (2016)","DOI":"10.1109\/CVPR.2016.182"},{"key":"5_CR54","unstructured":"Kinli, F.O., Mentes, S., Ozcan, B., Kirac, F., Timofte, R., et al.: Aim 2022 challenge on Instagram filter removal: methods and results. In: Proceedings of the European Conference on Computer Vision (ECCV) Workshops (2022)"},{"key":"5_CR55","doi-asserted-by":"crossref","unstructured":"Kong, F., et al.: Residual local feature network for efficient super-resolution. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 766\u2013776 (2022)","DOI":"10.1109\/CVPRW56347.2022.00092"},{"key":"5_CR56","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems, vol. 25 (2012)"},{"key":"5_CR57","doi-asserted-by":"crossref","unstructured":"Li, Y., Gu, S., Gool, L.V., Timofte, R.: Learning filter basis for convolutional neural network compression. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5623\u20135632 (2019)","DOI":"10.1109\/ICCV.2019.00572"},{"key":"5_CR58","unstructured":"Li, Y., et al.: Ntire 2022 challenge on efficient super-resolution: methods and results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1062\u20131102 (2022)"},{"key":"5_CR59","doi-asserted-by":"crossref","unstructured":"Lim, B., Son, S., Kim, H., Nah, S., Mu Lee, K.: Enhanced deep residual networks for single image super-resolution. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 136\u2013144 (2017)","DOI":"10.1109\/CVPRW.2017.151"},{"key":"5_CR60","doi-asserted-by":"crossref","unstructured":"Liu, Z., et al.: Metapruning: meta learning for automatic neural network channel pruning. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 3296\u20133305 (2019)","DOI":"10.1109\/ICCV.2019.00339"},{"key":"5_CR61","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1007\/978-3-030-01267-0_44","volume-title":"Computer Vision \u2013 ECCV 2018","author":"Z Liu","year":"2018","unstructured":"Liu, Z., Wu, B., Luo, W., Yang, X., Liu, W., Cheng, K.-T.: Bi-real net: enhancing the performance of 1-Bit CNNs with improved representational capability and advanced training algorithm. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11219, pp. 747\u2013763. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01267-0_44"},{"key":"5_CR62","unstructured":"Loshchilov, I., Hutter, F.: SGDR: Stochastic gradient descent with warm restarts. arXiv preprint arXiv:1608.03983 (2016)"},{"key":"5_CR63","unstructured":"Lugmayr, A., Danelljan, M., Timofte, R.: Ntire 2020 challenge on real-world image super-resolution: Methods and results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 494\u2013495 (2020)"},{"key":"5_CR64","doi-asserted-by":"crossref","unstructured":"Luo, Z., et al.: Fast nearest convolution for real-time efficient image super-resolution. In: Proceedings of the European Conference on Computer Vision (ECCV) Workshops (2022)","DOI":"10.1007\/978-3-031-25063-7_35"},{"key":"5_CR65","unstructured":"Obukhov, A., Rakhuba, M., Georgoulis, S., Kanakis, M., Dai, D., Van Gool, L.: T-basis: a compact representation for neural networks. In: International Conference on Machine Learning, pp. 7392\u20137404. PMLR (2020)"},{"issue":"3","key":"5_CR66","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/MSP.2003.1203207","volume":"20","author":"SC Park","year":"2003","unstructured":"Park, S.C., Park, M.K., Kang, M.G.: Super-resolution image reconstruction: a technical overview. IEEE Signal Process. Mag. 20(3), 21\u201336 (2003)","journal-title":"IEEE Signal Process. Mag."},{"key":"5_CR67","doi-asserted-by":"crossref","unstructured":"Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.C.: Mobilenetv 2: inverted residuals and linear bottlenecks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4510\u20134520 (2018)","DOI":"10.1109\/CVPR.2018.00474"},{"key":"5_CR68","doi-asserted-by":"crossref","unstructured":"Tan, M., et al.: MNASnet: platform-aware neural architecture search for mobile. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2820\u20132828 (2019)","DOI":"10.1109\/CVPR.2019.00293"},{"key":"5_CR69","unstructured":"TensorFlow-Lite: https:\/\/www.tensorflow.org\/lite"},{"key":"5_CR70","doi-asserted-by":"crossref","unstructured":"Timofte, R., Agustsson, E., Van Gool, L., Yang, M.H., Zhang, L.: Ntire 2017 challenge on single image super-resolution: methods and results. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 114\u2013125 (2017)","DOI":"10.1109\/CVPRW.2017.150"},{"key":"5_CR71","doi-asserted-by":"crossref","unstructured":"Timofte, R., De Smet, V., Van Gool, L.: Anchored neighborhood regression for fast example-based super-resolution. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1920\u20131927 (2013)","DOI":"10.1109\/ICCV.2013.241"},{"key":"5_CR72","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1007\/978-3-319-16817-3_8","volume-title":"Computer Vision \u2013 ACCV 2014","author":"R Timofte","year":"2015","unstructured":"Timofte, R., De\u00a0Smet, V., Van\u00a0Gool, L.: A+: adjusted anchored neighborhood regression for fast super-resolution. In: Cremers, D., Reid, I., Saito, H., Yang, M.-H. (eds.) ACCV 2014. LNCS, vol. 9006, pp. 111\u2013126. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-16817-3_8"},{"key":"5_CR73","unstructured":"Timofte, R., Gu, S., Wu, J., Van Gool, L.: Ntire 2018 challenge on single image super-resolution: methods and results. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 852\u2013863 (2018)"},{"key":"5_CR74","doi-asserted-by":"crossref","unstructured":"Timofte, R., Rothe, R., Van Gool, L.: Seven ways to improve example-based single image super resolution. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1865\u20131873 (2016)","DOI":"10.1109\/CVPR.2016.206"},{"key":"5_CR75","unstructured":"Uhlich, S., et al.: Mixed precision DNNs: All you need is a good parametrization. arXiv preprint arXiv:1905.11452 (2019)"},{"key":"5_CR76","doi-asserted-by":"crossref","unstructured":"Wan, A., et al.: Fbnetv2: differentiable neural architecture search for spatial and channel dimensions. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 12965\u201312974 (2020)","DOI":"10.1109\/CVPR42600.2020.01298"},{"key":"5_CR77","doi-asserted-by":"crossref","unstructured":"Wang, H., Chen, P., Zhuang, B., Shen, C.: Fully quantized image super-resolution networks. In: Proceedings of the 29th ACM International Conference on Multimedia, pp. 639\u2013647 (2021)","DOI":"10.1145\/3474085.3475227"},{"key":"5_CR78","doi-asserted-by":"crossref","unstructured":"Wang, Y., et al.: Towards compact single image super-resolution via contrastive self-distillation. arXiv preprint arXiv:2105.11683 (2021)","DOI":"10.24963\/ijcai.2021\/155"},{"key":"5_CR79","doi-asserted-by":"crossref","unstructured":"Wu, B., et al.: FBNet: hardware-aware efficient convnet design via differentiable neural architecture search. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10734\u201310742 (2019)","DOI":"10.1109\/CVPR.2019.01099"},{"key":"5_CR80","doi-asserted-by":"crossref","unstructured":"Yang, C.Y., Yang, M.H.: Fast direct super-resolution by simple functions. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 561\u2013568 (2013)","DOI":"10.1109\/ICCV.2013.75"},{"key":"5_CR81","unstructured":"Yang, J., Wright, J., Huang, T., Ma, Y.: Image super-resolution as sparse representation of raw image patches. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138. IEEE (2008)"},{"issue":"11","key":"5_CR82","doi-asserted-by":"publisher","first-page":"2861","DOI":"10.1109\/TIP.2010.2050625","volume":"19","author":"J Yang","year":"2010","unstructured":"Yang, J., Wright, J., Huang, T.S., Ma, Y.: Image super-resolution via sparse representation. IEEE Trans. Image Process. 19(11), 2861\u20132873 (2010)","journal-title":"IEEE Trans. Image Process."},{"key":"5_CR83","doi-asserted-by":"crossref","unstructured":"Yang, J., et al.: Quantization networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 7308\u20137316 (2019)","DOI":"10.1109\/CVPR.2019.00748"},{"key":"5_CR84","unstructured":"Yang, R., Timofte, R., et al.: Aim 2022 challenge on super-resolution of compressed image and video: Dataset, methods and results. In: Proceedings of the European Conference on Computer Vision (ECCV) Workshops (2022)"},{"key":"5_CR85","unstructured":"Zagoruyko, S., Komodakis, N.: DiracNets: Training very deep neural networks without skip-connections. arXiv preprint arXiv:1706.00388 (2017)"},{"key":"5_CR86","unstructured":"Zhang, K., Gu, S., Timofte, R.: Ntire 2020 challenge on perceptual extreme super-resolution: methods and results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 492\u2013493 (2020)"},{"key":"5_CR87","first-page":"18795","volume":"33","author":"J Zhuang","year":"2020","unstructured":"Zhuang, J., et al.: Adabelief optimizer: adapting stepsizes by the belief in observed gradients. Adv. Neural. Inf. Process. Syst. 33, 18795\u201318806 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2022 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-25066-8_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,14]],"date-time":"2024-10-14T13:13:54Z","timestamp":1728911634000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-25066-8_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031250651","9783031250668"],"references-count":87,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-25066-8_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"18 February 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tel Aviv","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Israel","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2022.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5804","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1645","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.21","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.91","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"From the workshops, 367 reviewed full papers have been selected for publication","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}