{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T08:53:12Z","timestamp":1765356792221,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":39,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Christian Doppler Laboratory ATHENA"},{"name":"FWF Austrian Science Fund under grant P 31486-N31"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,12]]},"DOI":"10.1145\/3394171.3413658","type":"proceedings-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T13:10:18Z","timestamp":1602508218000},"page":"3577-3585","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":19,"title":["Relevance-Based Compression of Cataract Surgery Videos Using Convolutional Neural Networks"],"prefix":"10.1145","author":[{"given":"Negin","family":"Ghamsarian","sequence":"first","affiliation":[{"name":"Alpen-Adria University of Klagenfurt, Klagenfurt, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hadi","family":"Amirpourazarian","sequence":"additional","affiliation":[{"name":"Alpen-Adria-Universitat Klagenfurt, Klagenfurt, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christian","family":"Timmerer","sequence":"additional","affiliation":[{"name":"Alpen-Adria-Universitat Klagenfurt, Klagenfurt, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mario","family":"Taschwer","sequence":"additional","affiliation":[{"name":"Klagenfurt University, Klagenfurt, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Klaus","family":"Sch\u00f6ffmann","sequence":"additional","affiliation":[{"name":"Klagenfurt University, Klagenfurt, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"e_1_3_2_2_1_1","unstructured":"Waleed Abdulla. 2017. Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow. https:\/\/github.com\/matterport\/Mask_RCNN.  Waleed Abdulla. 2017. Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow. https:\/\/github.com\/matterport\/Mask_RCNN."},{"key":"e_1_3_2_2_2_1","unstructured":"Anurag Arnab and Philip H. S. Torr. 2017. Pixelwise Instance Segmentation with a Dynamically Instantiated Network. CoRR Vol. abs\/1704.02386 (2017). arxiv: 1704.02386 http:\/\/arxiv.org\/abs\/1704.02386  Anurag Arnab and Philip H. S. Torr. 2017. Pixelwise Instance Segmentation with a Dynamically Instantiated Network. CoRR Vol. abs\/1704.02386 (2017). arxiv: 1704.02386 http:\/\/arxiv.org\/abs\/1704.02386"},{"key":"e_1_3_2_2_3_1","unstructured":"Min Bai and Raquel Urtasun. 2016. Deep Watershed Transform for Instance Segmentation. CoRR Vol. abs\/1611.08303 (2016). arxiv: 1611.08303 http:\/\/arxiv.org\/abs\/1611.08303  Min Bai and Raquel Urtasun. 2016. Deep Watershed Transform for Instance Segmentation. CoRR Vol. abs\/1611.08303 (2016). arxiv: 1611.08303 http:\/\/arxiv.org\/abs\/1611.08303"},{"key":"e_1_3_2_2_4_1","unstructured":"F. Bossen et almbox. 2013. Common test conditions and software reference configurations. JCTVC-L1100 Vol. 12 (2013) 7.  F. Bossen et almbox. 2013. Common test conditions and software reference configurations. JCTVC-L1100 Vol. 12 (2013) 7."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2960869"},{"volume-title":"International ophthalmology","year":"1998","author":"Castells Xavier","key":"e_1_3_2_2_6_1"},{"key":"e_1_3_2_2_7_1","unstructured":"Liang-Chieh Chen Alexander Hermans George Papandreou Florian Schroff Peng Wang and Hartwig Adam. 2017. MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features. CoRR Vol. abs\/1712.04837 (2017). arxiv: 1712.04837 http:\/\/arxiv.org\/abs\/1712.04837  Liang-Chieh Chen Alexander Hermans George Papandreou Florian Schroff Peng Wang and Hartwig Adam. 2017. MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features. CoRR Vol. abs\/1712.04837 (2017). arxiv: 1712.04837 http:\/\/arxiv.org\/abs\/1712.04837"},{"key":"e_1_3_2_2_8_1","unstructured":"Jifeng Dai Yi Li Kaiming He and Jian Sun. 2016. R-FCN: Object Detection via Region-based Fully Convolutional Networks. CoRR Vol. abs\/1605.06409 (2016). arxiv: 1605.06409 http:\/\/arxiv.org\/abs\/1605.06409  Jifeng Dai Yi Li Kaiming He and Jian Sun. 2016. R-FCN: Object Detection via Region-based Fully Convolutional Networks. CoRR Vol. abs\/1605.06409 (2016). arxiv: 1605.06409 http:\/\/arxiv.org\/abs\/1605.06409"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"crossref","unstructured":"J. Deng W. Dong R. Socher L.-J. Li K. Li and L. Fei-Fei. 2009. ImageNet: A Large-Scale Hierarchical Image Database. In CVPR09.  J. Deng W. Dong R. Socher L.-J. Li K. Li and L. Fei-Fei. 2009. ImageNet: A Large-Scale Hierarchical Image Database. In CVPR09.","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_3_2_2_10_1","unstructured":"Alireza Fathi Zbigniew Wojna Vivek Rathod Peng Wang Hyun Oh Song Sergio Guadarrama and Kevin P. Murphy. 2017. Semantic Instance Segmentation via Deep Metric Learning. CoRR Vol. abs\/1703.10277 (2017). arxiv: 1703.10277 http:\/\/arxiv.org\/abs\/1703.10277  Alireza Fathi Zbigniew Wojna Vivek Rathod Peng Wang Hyun Oh Song Sergio Guadarrama and Kevin P. Murphy. 2017. Semantic Instance Segmentation via Deep Metric Learning. CoRR Vol. abs\/1703.10277 (2017). arxiv: 1703.10277 http:\/\/arxiv.org\/abs\/1703.10277"},{"key":"e_1_3_2_2_11_1","unstructured":"Patrick Follmann and Rebecca K\u00f6nig. 2019. Oriented Boxes for Accurate Instance Segmentation. arxiv: cs.CV\/1911.07732  Patrick Follmann and Rebecca K\u00f6nig. 2019. Oriented Boxes for Accurate Instance Segmentation. arxiv: cs.CV\/1911.07732"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3372278.3391937"},{"volume":"3","volume-title":"2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society","author":"Gokturk S. B.","key":"e_1_3_2_2_13_1"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2013.2282897"},{"key":"e_1_3_2_2_15_1","unstructured":"Adam W. Harley Konstantinos G. Derpanis and Iasonas Kokkinos. 2017. Segmentation-Aware Convolutional Networks Using Local Attention Masks. CoRR Vol. abs\/1708.04607 (2017). arxiv: 1708.04607 http:\/\/arxiv.org\/abs\/1708.04607  Adam W. Harley Konstantinos G. Derpanis and Iasonas Kokkinos. 2017. Segmentation-Aware Convolutional Networks Using Local Attention Masks. CoRR Vol. abs\/1708.04607 (2017). arxiv: 1708.04607 http:\/\/arxiv.org\/abs\/1708.04607"},{"volume-title":"Mask R-CNN. In The IEEE International Conference on Computer Vision (ICCV).","year":"2017","author":"He Kaiming","key":"e_1_3_2_2_16_1"},{"volume-title":"Deep Residual Learning for Image Recognition. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 770--778","author":"He K.","key":"e_1_3_2_2_17_1"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"crossref","unstructured":"Qiang Hu Jun Zhou Xiaoyun Zhang Zhiyong Gao and Ming-Ting Sun. 2018. In-loop perceptual model-based rate-distortion optimization for HEVC real-time encoder. Journal of Real-Time Image Processing (04 2018) 1--19. https:\/\/doi.org\/10.1007\/s11554-018-0772-1  Qiang Hu Jun Zhou Xiaoyun Zhang Zhiyong Gao and Ming-Ting Sun. 2018. In-loop perceptual model-based rate-distortion optimization for HEVC real-time encoder. Journal of Real-Time Image Processing (04 2018) 1--19. https:\/\/doi.org\/10.1007\/s11554-018-0772-1","DOI":"10.1007\/s11554-018-0772-1"},{"key":"e_1_3_2_2_19_1","unstructured":"Zhaojin Huang Lichao Huang Yongchao Gong Chang Huang and Xinggang Wang. 2019. Mask Scoring R-CNN. CoRR Vol. abs\/1903.00241 (2019). arxiv: 1903.00241 http:\/\/arxiv.org\/abs\/1903.00241  Zhaojin Huang Lichao Huang Yongchao Gong Chang Huang and Xinggang Wang. 2019. Mask Scoring R-CNN. CoRR Vol. abs\/1903.00241 (2019). arxiv: 1903.00241 http:\/\/arxiv.org\/abs\/1903.00241"},{"key":"e_1_3_2_2_20_1","unstructured":"Alexander Kirillov Evgeny Levinkov Bjoern Andres Bogdan Savchynskyy and Carsten Rother. 2016. InstanceCut: from Edges to Instances with MultiCut. CoRR Vol. abs\/1611.08272 (2016). arxiv: 1611.08272 http:\/\/arxiv.org\/abs\/1611.08272  Alexander Kirillov Evgeny Levinkov Bjoern Andres Bogdan Savchynskyy and Carsten Rother. 2016. InstanceCut: from Edges to Instances with MultiCut. CoRR Vol. abs\/1611.08272 (2016). arxiv: 1611.08272 http:\/\/arxiv.org\/abs\/1611.08272"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"crossref","unstructured":"L'ubor Ladick\u00fd Paul Sturgess Karteek Alahari Chris Russell and Philip H. S. Torr. 2010. What Where and How Many? Combining Object Detectors and CRFs. In Computer Vision -- ECCV 2010 Kostas Daniilidis Petros Maragos and Nikos Paragios (Eds.). Springer Berlin Heidelberg Berlin Heidelberg 424--437.  L'ubor Ladick\u00fd Paul Sturgess Karteek Alahari Chris Russell and Philip H. S. Torr. 2010. What Where and How Many? Combining Object Detectors and CRFs. In Computer Vision -- ECCV 2010 Kostas Daniilidis Petros Maragos and Nikos Paragios (Eds.). Springer Berlin Heidelberg Berlin Heidelberg 424--437.","DOI":"10.1007\/978-3-642-15561-1_31"},{"key":"e_1_3_2_2_22_1","unstructured":"Guanbin Li and Yizhou Yu. 2016. Visual Saliency Detection Based on Multiscale Deep CNN Features. CoRR Vol. abs\/1609.02077 (2016). arxiv: 1609.02077 http:\/\/arxiv.org\/abs\/1609.02077  Guanbin Li and Yizhou Yu. 2016. Visual Saliency Detection Based on Multiscale Deep CNN Features. CoRR Vol. abs\/1609.02077 (2016). arxiv: 1609.02077 http:\/\/arxiv.org\/abs\/1609.02077"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2015.04.011"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2010.07.001"},{"key":"e_1_3_2_2_25_1","unstructured":"Tsung-Yi Lin Michael Maire Serge J. Belongie Lubomir D. Bourdev Ross B. Girshick James Hays Pietro Perona Deva Ramanan Piotr Doll\u00e1 r and C. Lawrence Zitnick. 2014. Microsoft COCO: Common Objects in Context. CoRR Vol. abs\/1405.0312 (2014). arxiv: 1405.0312 http:\/\/arxiv.org\/abs\/1405.0312  Tsung-Yi Lin Michael Maire Serge J. Belongie Lubomir D. Bourdev Ross B. Girshick James Hays Pietro Perona Deva Ramanan Piotr Doll\u00e1 r and C. Lawrence Zitnick. 2014. Microsoft COCO: Common Objects in Context. CoRR Vol. abs\/1405.0312 (2014). arxiv: 1405.0312 http:\/\/arxiv.org\/abs\/1405.0312"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.70"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2007.913754"},{"key":"e_1_3_2_2_28_1","unstructured":"Jonathan Long Evan Shelhamer and Trevor Darrell. 2014. Fully Convolutional Networks for Semantic Segmentation. CoRR Vol. abs\/1411.4038 (2014). arxiv: 1411.4038 http:\/\/arxiv.org\/abs\/1411.4038  Jonathan Long Evan Shelhamer and Trevor Darrell. 2014. Fully Convolutional Networks for Semantic Segmentation. CoRR Vol. abs\/1411.4038 (2014). arxiv: 1411.4038 http:\/\/arxiv.org\/abs\/1411.4038"},{"volume-title":"Investigation of the Impact of Compression on the Perceptional Quality of Laparoscopic Videos. In 2014 IEEE 27th International Symposium on Computer Based Medical Systems. 153--158","author":"M\u00fcnzer B.","key":"e_1_3_2_2_29_1"},{"key":"e_1_3_2_2_30_1","unstructured":"Negin Ghamsarian Mario Taschwer and Klaus Schoeffmann. 2020. Deblurring cataract surgery videos using a multi-scale deconvolutional neural network. CoRR Vol. abs\/1504.06852 (2020). arxiv: 1504.06852 http:\/\/arxiv.org\/abs\/1504.06852  Negin Ghamsarian Mario Taschwer and Klaus Schoeffmann. 2020. Deblurring cataract surgery videos using a multi-scale deconvolutional neural network. CoRR Vol. abs\/1504.06852 (2020). arxiv: 1504.06852 http:\/\/arxiv.org\/abs\/1504.06852"},{"volume-title":"Associative Embedding: End-to-End Learning for Joint Detection and Grouping. CoRR","year":"2016","author":"Newell Alejandro","key":"e_1_3_2_2_31_1"},{"key":"e_1_3_2_2_32_1","article-title":"JPEG2000: Image Compression Fundamentals, Standards and Practice","volume":"11","author":"Rabbani Majid","year":"2002","journal-title":"Journal of Electronic Imaging"},{"key":"e_1_3_2_2_33_1","unstructured":"Shaoqing Ren Kaiming He Ross B. Girshick and Jian Sun. 2015. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. CoRR Vol. abs\/1506.01497 (2015). arxiv: 1506.01497 http:\/\/arxiv.org\/abs\/1506.01497  Shaoqing Ren Kaiming He Ross B. Girshick and Jian Sun. 2015. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. CoRR Vol. abs\/1506.01497 (2015). arxiv: 1506.01497 http:\/\/arxiv.org\/abs\/1506.01497"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3204949.3208137"},{"volume-title":"2008 IEEE Conference on Computer Vision and Pattern Recognition. 1--8.","author":"Shotton J.","key":"e_1_3_2_2_35_1"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2012.2221191"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"crossref","unstructured":"Sameer Trikha Andrew Turnbull R.J. Morris David Anderson and Parwez Hossain. 2013. hrefhttps:\/\/www.ncbi.nlm.nih.gov\/pubmed\/23370418The journey to femtosecond laser-assisted cataract surgery: New beginnings or a false dawn? Eye (London England) Vol. 27 (02 2013). https:\/\/doi.org\/10.1038\/eye.2012.293  Sameer Trikha Andrew Turnbull R.J. Morris David Anderson and Parwez Hossain. 2013. hrefhttps:\/\/www.ncbi.nlm.nih.gov\/pubmed\/23370418The journey to femtosecond laser-assisted cataract surgery: New beginnings or a false dawn? Eye (London England) Vol. 27 (02 2013). https:\/\/doi.org\/10.1038\/eye.2012.293","DOI":"10.1038\/eye.2012.293"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2014.2314864"},{"volume-title":"Pattern Recognition,","author":"Zhu Yuanping","key":"e_1_3_2_2_39_1"}],"event":{"name":"MM '20: The 28th ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Seattle WA USA","acronym":"MM '20"},"container-title":["Proceedings of the 28th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413658","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394171.3413658","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:47:16Z","timestamp":1750193236000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3413658"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":39,"alternative-id":["10.1145\/3394171.3413658","10.1145\/3394171"],"URL":"https:\/\/doi.org\/10.1145\/3394171.3413658","relation":{},"subject":[],"published":{"date-parts":[[2020,10,12]]},"assertion":[{"value":"2020-10-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}