{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:29:01Z","timestamp":1760956141883,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":59,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,12,19]],"date-time":"2021-12-19T00:00:00Z","timestamp":1639872000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Science and Engineering Research Board (SERB)","award":["EMR\/2017\/003542"],"award-info":[{"award-number":["EMR\/2017\/003542"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,12,19]]},"DOI":"10.1145\/3490035.3490266","type":"proceedings-article","created":{"date-parts":[[2021,12,14]],"date-time":"2021-12-14T23:15:16Z","timestamp":1639523716000},"page":"1-9","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["HDRVideo-GAN"],"prefix":"10.1145","author":[{"given":"Mrinal","family":"Anand","sequence":"first","affiliation":[{"name":"Indian Institute of Technology, Gandhinagar, Gujarat, India"}]},{"given":"Nidhin","family":"Harilal","sequence":"additional","affiliation":[{"name":"University of Colorado"}]},{"given":"Chandan","family":"Kumar","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology, Gandhinagar, Gujarat, India"}]},{"given":"Shanmuganathan","family":"Raman","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology, Gandhinagar, Gujarat, India"}]}],"member":"320","published-online":{"date-parts":[[2021,12,19]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2816795.2818107"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.1996.506947"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/258734.258884"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401132.1401174"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3130800.3130816"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2019.01143"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"Philipp Fischer Alexey Dosovitskiy Eddy Ilg Philip H\u00e4usser Caner Haz\u0131rba\u015f Vladimir Golkov Patrick van der Smagt Daniel Cremers and Thomas Brox. 2015. FlowNet: Learning Optical Flow with Convolutional Networks. arXiv:1504.06852 [cs.CV]  Philipp Fischer Alexey Dosovitskiy Eddy Ilg Philip H\u00e4usser Caner Haz\u0131rba\u015f Vladimir Golkov Patrick van der Smagt Daniel Cremers and Thomas Brox. 2015. FlowNet: Learning Optical Flow with Convolutional Networks. arXiv:1504.06852 [cs.CV]","DOI":"10.1109\/ICCV.2015.316"},{"key":"e_1_3_2_1_8_1","volume-title":"Digital Photography X","volume":"9023","author":"Froehlich Jan","year":"2014","unstructured":"Jan Froehlich , Stefan Grandinetti , Bernd Eberhardt , Simon Walter , Andreas Schilling , and Harald Brendel . 2014 . Creating cinematic wide gamut HDR-video for the evaluation of tone mapping operators and HDR-displays . In Digital Photography X , Vol. 9023 . International Society for Optics and Photonics, 90230X. Jan Froehlich, Stefan Grandinetti, Bernd Eberhardt, Simon Walter, Andreas Schilling, and Harald Brendel. 2014. Creating cinematic wide gamut HDR-video for the evaluation of tone mapping operators and HDR-displays. In Digital Photography X, Vol. 9023. International Society for Optics and Photonics, 90230X."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2015.7301366"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.5555\/2858834.2858847"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2980179.2980254"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2010.579"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.154"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00936"},{"volume-title":"IEEE Conference on Computer Vision and Pattern Recognition (CVPR). http:\/\/lmb.informatik.unifreiburg.de\/\/Publications\/2017\/IMKDB17","author":"Ilg E.","key":"e_1_3_2_1_15_1","unstructured":"E. Ilg , N. Mayer , T. Saikia , M. Keuper , A. Dosovitskiy , and T. Brox . 2017. FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks . In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). http:\/\/lmb.informatik.unifreiburg.de\/\/Publications\/2017\/IMKDB17 E. Ilg, N. Mayer, T. Saikia, M. Keuper, A. Dosovitskiy, and T. Brox. 2017. FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). http:\/\/lmb.informatik.unifreiburg.de\/\/Publications\/2017\/IMKDB17"},{"key":"e_1_3_2_1_16_1","volume-title":"Self-Supervised Feature Learning by Learning to Spot Artifacts. CoRR abs\/1806.05024","author":"Jenni Simon","year":"2018","unstructured":"Simon Jenni and Paolo Favaro . 2018. Self-Supervised Feature Learning by Learning to Spot Artifacts. CoRR abs\/1806.05024 ( 2018 ). arXiv:1806.05024 http:\/\/arxiv.org\/abs\/1806.05024 Simon Jenni and Paolo Favaro. 2018. Self-Supervised Feature Learning by Learning to Spot Artifacts. CoRR abs\/1806.05024 (2018). arXiv:1806.05024 http:\/\/arxiv.org\/abs\/1806.05024"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3072959.3073609"},{"volume-title":"Computer Graphics Forum","author":"Kalantari Nima Khademi","key":"e_1_3_2_1_19_1","unstructured":"Nima Khademi Kalantari and Ravi Ramamoorthi . 2019. Deep HDR Video from Sequences with Alternating Exposures . In Computer Graphics Forum , Vol. 38 . Wiley Online Library , 193--205. Nima Khademi Kalantari and Ravi Ramamoorthi. 2019. Deep HDR Video from Sequences with Alternating Exposures. In Computer Graphics Forum, Vol. 38. Wiley Online Library, 193--205."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2508363.2508402"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/882262.882270"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2006.312892"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCPhot.2013.6528315"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2013.08.018"},{"key":"e_1_3_2_1_25_1","volume-title":"Self-supervised Learning for Video Correspondence Flow. CoRR abs\/1905.00875","author":"Lai Zihang","year":"2019","unstructured":"Zihang Lai and Weidi Xie . 2019. Self-supervised Learning for Video Correspondence Flow. CoRR abs\/1905.00875 ( 2019 ). arXiv:1905.00875 http:\/\/arxiv.org\/abs\/1905.00875 Zihang Lai and Weidi Xie. 2019. Self-supervised Learning for Video Correspondence Flow. CoRR abs\/1905.00875 (2019). arXiv:1905.00875 http:\/\/arxiv.org\/abs\/1905.00875"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.5555\/3454287.3454913"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2642790"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2661229.2661277"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.5555\/1623264.1623280"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2671921"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2011.6115678"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/641007.641032"},{"key":"e_1_3_2_1_33_1","first-page":"2","article-title":"Being undigital with digital cameras","volume":"1","author":"Mann S","year":"1994","unstructured":"S Mann and R Picard . 1994 . Being undigital with digital cameras . MIT Media Lab Perceptual 1 (1994), 2 . S Mann and R Picard. 1994. Being undigital with digital cameras. MIT Media Lab Perceptual 1 (1994), 2.","journal-title":"MIT Media Lab Perceptual"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/2010324.1964935"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2010324.1964935"},{"volume-title":"Computer Graphics Forum","author":"Marnerides Demetris","key":"e_1_3_2_1_36_1","unstructured":"Demetris Marnerides , Thomas Bashford-Rogers , Jonathan Hatchett , and Kurt Debattista . 2018. ExpandNet: A deep convolutional neural network for high dynamic range expansion from low dynamic range content . In Computer Graphics Forum , Vol. 37 . Wiley Online Library , 37--49. Demetris Marnerides, Thomas Bashford-Rogers, Jonathan Hatchett, and Kurt Debattista. 2018. ExpandNet: A deep convolutional neural network for high dynamic range expansion from low dynamic range content. In Computer Graphics Forum, Vol. 37. Wiley Online Library, 37--49."},{"key":"e_1_3_2_1_37_1","unstructured":"Daniel Maurer and Andr\u00e9s Bruhn. 2018. ProFlow: Learning to Predict Optical Flow. arXiv:1806.00800 [cs.CV]  Daniel Maurer and Andr\u00e9s Bruhn. 2018. ProFlow: Learning to Predict Optical Flow. arXiv:1806.00800 [cs.CV]"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553469"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2000.855857"},{"key":"e_1_3_2_1_40_1","volume-title":"Robust high dynamic range imaging by rank minimization","author":"Oh Tae-Hyun","year":"2014","unstructured":"Tae-Hyun Oh , Joon-Young Lee , Yu-Wing Tai , and In So Kweon . 2014. Robust high dynamic range imaging by rank minimization . IEEE transactions on pattern analysis and machine intelligence 37, 6 ( 2014 ), 1219--1232. Tae-Hyun Oh, Joon-Young Lee, Yu-Wing Tai, and In So Kweon. 2014. Robust high dynamic range imaging by rank minimization. IEEE transactions on pattern analysis and machine intelligence 37, 6 (2014), 1219--1232."},{"volume-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2720--2729","author":"Ranjan A.","key":"e_1_3_2_1_41_1","unstructured":"A. Ranjan and M. J. Black . 2017. Optical Flow Estimation Using a Spatial Pyramid Network . In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2720--2729 . A. Ranjan and M. J. Black. 2017. Optical Flow Estimation Using a Spatial Pyramid Network. In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2720--2729."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"crossref","unstructured":"Olaf Ronneberger Philipp Fischer and Thomas Brox. 2015. U-Net: Convolutional Networks for Biomedical Image Segmentation. arXiv:1505.04597 [cs.CV]  Olaf Ronneberger Philipp Fischer and Thomas Brox. 2015. U-Net: Convolutional Networks for Biomedical Image Segmentation. arXiv:1505.04597 [cs.CV]","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_43"},{"key":"e_1_3_2_1_44_1","first-page":"223","article-title":"HDRC-imagers for natural visual perception","volume":"1","author":"Seger Ulrich","year":"1999","unstructured":"Ulrich Seger , Uwe Apel , and Bernd H\u00f6fflinger . 1999 . HDRC-imagers for natural visual perception . Handbook of Computer Vision and Application 1 (1999), 223 -- 235 . Ulrich Seger, Uwe Apel, and Bernd H\u00f6fflinger. 1999. HDRC-imagers for natural visual perception. Handbook of Computer Vision and Application 1 (1999), 223--235.","journal-title":"Handbook of Computer Vision and Application"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/2366145.2366222"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.5555\/2968826.2968890"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/CRV.2019.00033"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/2010324.1964936"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/2010324.1964936"},{"key":"e_1_3_2_1_50_1","unstructured":"Anna Tomaszewska and Radoslaw Mantiuk. 2007. Image registration for multi-exposure high dynamic range image acquisition. (2007).  Anna Tomaszewska and Radoslaw Mantiuk. 2007. Image registration for multi-exposure high dynamic range image acquisition. (2007)."},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1080\/10867651.2003.10487583"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"crossref","unstructured":"Jun Xu Yuan Huang Ming-Ming Cheng Li Liu Fan Zhu Zhou Xu and Ling Shao. 2019. Noisy-As-Clean: Learning Self-supervised Denoising from the Corrupted Image. arXiv:1906.06878 [cs.CV]  Jun Xu Yuan Huang Ming-Ming Cheng Li Liu Fan Zhu Zhou Xu and Ling Shao. 2019. Noisy-As-Clean: Learning Self-supervised Denoising from the Corrupted Image. arXiv:1906.06878 [cs.CV]","DOI":"10.1109\/TIP.2020.3026622"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.484"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5540171"},{"key":"e_1_3_2_1_55_1","volume-title":"Efros","author":"Zhang Richard","year":"2016","unstructured":"Richard Zhang , Phillip Isola , and Alexei A . Efros . 2016 . Colorful Image Colorization. CoRR abs\/1603.08511 (2016). arXiv:1603.08511 http:\/\/arxiv.org\/abs\/1603.08511 Richard Zhang, Phillip Isola, and Alexei A. Efros. 2016. Colorful Image Colorization. CoRR abs\/1603.08511 (2016). arXiv:1603.08511 http:\/\/arxiv.org\/abs\/1603.08511"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCPHOT.2015.7168378"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2013.2283401"},{"key":"e_1_3_2_1_58_1","volume-title":"Lipschitz Generative Adversarial Nets. CoRR abs\/1902.05687","author":"Zhou Zhiming","year":"2019","unstructured":"Zhiming Zhou , Jiadong Liang , Yuxuan Song , Lantao Yu , Hongwei Wang , Weinan Zhang , Yong Yu , and Zhihua Zhang . 2019. Lipschitz Generative Adversarial Nets. CoRR abs\/1902.05687 ( 2019 ). arXiv:1902.05687 http:\/\/arxiv.org\/abs\/1902.05687 Zhiming Zhou, Jiadong Liang, Yuxuan Song, Lantao Yu, Hongwei Wang, Weinan Zhang, Yong Yu, and Zhihua Zhang. 2019. Lipschitz Generative Adversarial Nets. CoRR abs\/1902.05687 (2019). arXiv:1902.05687 http:\/\/arxiv.org\/abs\/1902.05687"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"}],"event":{"name":"ICVGIP '21: Indian Conference on Computer Vision, Graphics and Image Processing","acronym":"ICVGIP '21","location":"Jodhpur India"},"container-title":["Proceedings of the Twelfth Indian Conference on Computer Vision, Graphics and Image Processing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3490035.3490266","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3490035.3490266","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:31:22Z","timestamp":1750188682000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3490035.3490266"}},"subtitle":["deep generative HDR video reconstruction"],"short-title":[],"issued":{"date-parts":[[2021,12,19]]},"references-count":59,"alternative-id":["10.1145\/3490035.3490266","10.1145\/3490035"],"URL":"https:\/\/doi.org\/10.1145\/3490035.3490266","relation":{},"subject":[],"published":{"date-parts":[[2021,12,19]]},"assertion":[{"value":"2021-12-19","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}