{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T15:38:58Z","timestamp":1780501138346,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":57,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T00:00:00Z","timestamp":1665360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,10]]},"DOI":"10.1145\/3503161.3548038","type":"proceedings-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T15:42:46Z","timestamp":1665416566000},"page":"6473-6482","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":49,"title":["TSRFormer"],"prefix":"10.1145","author":[{"given":"Weihong","family":"Lin","sequence":"first","affiliation":[{"name":"Microsoft Research Aisa, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zheng","family":"Sun","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences &amp; CASIA, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chixiang","family":"Ma","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingze","family":"Li","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiawei","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Sun","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Huo","sequence":"additional","affiliation":[{"name":"Microsoft Research Asia, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,10,10]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"e_1_3_2_2_2_1","volume-title":"Complicated table structure recognition. arXiv preprint arXiv:1908.04729","author":"Chi Zewen","year":"2019","unstructured":"Zewen Chi , Heyan Huang , Heng-Da Xu , Houjin Yu , Wanxuan Yin , and Xian- Ling Mao . 2019. Complicated table structure recognition. arXiv preprint arXiv:1908.04729 ( 2019 ). Zewen Chi, Heyan Huang, Heng-Da Xu, Houjin Yu, Wanxuan Yin, and Xian- Ling Mao. 2019. Complicated table structure recognition. arXiv preprint arXiv:1908.04729 (2019)."},{"key":"e_1_3_2_2_3_1","volume-title":"2019 International Conference on Document Analysis and Recognition (ICDAR). IEEE, 894--901","author":"Deng Yuntian","year":"2019","unstructured":"Yuntian Deng , David Rosenberg , and Gideon Mann . 2019 . Challenges in endto- end neural scientific table recognition . In 2019 International Conference on Document Analysis and Recognition (ICDAR). IEEE, 894--901 . Yuntian Deng, David Rosenberg, and Gideon Mann. 2019. Challenges in endto- end neural scientific table recognition. In 2019 International Conference on Document Analysis and Recognition (ICDAR). IEEE, 894--901."},{"key":"e_1_3_2_2_4_1","volume-title":"ICDAR 2019 competition on table detection and recognition (cTDaR). In 2019 International Conference on Document Analysis and Recognition (ICDAR). IEEE, 1510--1515","author":"Gao Liangcai","year":"2019","unstructured":"Liangcai Gao , Yilun Huang , Herv\u00e9 D\u00e9jean , Jean-Luc Meunier , Qinqin Yan , Yu Fang , Florian Kleber , and Eva Lang . 2019 . ICDAR 2019 competition on table detection and recognition (cTDaR). In 2019 International Conference on Document Analysis and Recognition (ICDAR). IEEE, 1510--1515 . Liangcai Gao, Yilun Huang, Herv\u00e9 D\u00e9jean, Jean-Luc Meunier, Qinqin Yan, Yu Fang, Florian Kleber, and Eva Lang. 2019. ICDAR 2019 competition on table detection and recognition (cTDaR). In 2019 International Conference on Document Analysis and Recognition (ICDAR). IEEE, 1510--1515."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00360"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2361354.2361365"},{"key":"e_1_3_2_2_7_1","volume-title":"ICDAR 2013 table competition. In 2013 12th International Conference on Document Analysis and Recognition. IEEE, 1449--1453","author":"G\u00f6bel Max","year":"2013","unstructured":"Max G\u00f6bel , Tamir Hassan , Ermelinda Oro , and Giorgio Orsi . 2013 . ICDAR 2013 table competition. In 2013 12th International Conference on Document Analysis and Recognition. IEEE, 1449--1453 . Max G\u00f6bel, Tamir Hassan, Ermelinda Oro, and Giorgio Orsi. 2013. ICDAR 2013 table competition. In 2013 12th International Conference on Document Analysis and Recognition. IEEE, 1449--1453."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3103413"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"e_1_3_2_2_10_1","volume-title":"Deep Residual Learning for Image Recognition. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 770--778","author":"He Kaiming","year":"2016","unstructured":"Kaiming He , Xiangyu Zhang , Shaoqing Ren , and Jian Sun . 2016 . Deep Residual Learning for Image Recognition. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 770--778 . https:\/\/doi.org\/10.1109\/CVPR.2016.90 Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 770--778. https:\/\/doi.org\/10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_2_11_1","volume-title":"PingAn-VCGroup's Solution for ICDAR 2021 Competition on Scientific Table Image Recognition to Latex. arXiv preprint arXiv:2105.01846","author":"He Yelin","year":"2021","unstructured":"Yelin He , Xianbiao Qi , Jiaquan Ye , Peng Gao , Yihao Chen , Bingcong Li , Xin Tang , and Rong Xiao . 2021. PingAn-VCGroup's Solution for ICDAR 2021 Competition on Scientific Table Image Recognition to Latex. arXiv preprint arXiv:2105.01846 ( 2021 ). Yelin He, Xianbiao Qi, Jiaquan Ye, Peng Gao, Yihao Chen, Bingcong Li, Xin Tang, and Rong Xiao. 2021. PingAn-VCGroup's Solution for ICDAR 2021 Competition on Scientific Table Image Recognition to Latex. arXiv preprint arXiv:2105.01846 (2021)."},{"key":"e_1_3_2_2_12_1","unstructured":"Katsuhiko Itonori. 1993. Table structure recognition based on textblock arrangement and ruled line position. In ICDAR. 765--768.  Katsuhiko Itonori. 1993. Table structure recognition based on textblock arrangement and ruled line position. In ICDAR. 765--768."},{"key":"e_1_3_2_2_13_1","volume-title":"Muhammad Ali Shahzad, and Faisal Shafait.","author":"Khan Saqib Ali","year":"2019","unstructured":"Saqib Ali Khan , Syed Muhammad Daniyal Khalid , Muhammad Ali Shahzad, and Faisal Shafait. 2019 . Table structure extraction with bi-directional gated recurrent unit networks. In ICDAR. 1366--1371. Saqib Ali Khan, Syed Muhammad Daniyal Khalid, Muhammad Ali Shahzad, and Faisal Shafait. 2019. Table structure extraction with bi-directional gated recurrent unit networks. In ICDAR. 1366--1371."},{"key":"e_1_3_2_2_14_1","volume-title":"International Workshop on Document Analysis Systems. Springer, 255--270","author":"Kieninger Thomas","year":"1998","unstructured":"Thomas Kieninger and Andreas Dengel . 1998 . The t-recs table recognition and analysis system . In International Workshop on Document Analysis Systems. Springer, 255--270 . Thomas Kieninger and Andreas Dengel. 1998. The t-recs table recognition and analysis system. In International Workshop on Document Analysis Systems. Springer, 255--270."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.1992.201803"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_45"},{"key":"e_1_3_2_2_17_1","volume-title":"DN-DETR: Accelerate DETR Training by Introducing Query DeNoising. arXiv preprint arXiv:2203.01305","author":"Li Feng","year":"2022","unstructured":"Feng Li , Hao Zhang , Shilong Liu , Jian Guo , Lionel M Ni , and Lei Zhang . 2022. DN-DETR: Accelerate DETR Training by Introducing Query DeNoising. arXiv preprint arXiv:2203.01305 ( 2022 ). Feng Li, Hao Zhang, Shilong Liu, Jian Guo, Lionel M Ni, and Lei Zhang. 2022. DN-DETR: Accelerate DETR Training by Introducing Query DeNoising. arXiv preprint arXiv:2203.01305 (2022)."},{"key":"e_1_3_2_2_18_1","volume-title":"Proceedings of The 12th language resources and evaluation conference. 1918--1925","author":"Li Minghao","year":"2020","unstructured":"Minghao Li , Lei Cui , Shaohan Huang , FuruWei, Ming Zhou , and Zhoujun Li . 2020 . Tablebank: Table benchmark for image-based table detection and recognition . In Proceedings of The 12th language resources and evaluation conference. 1918--1925 . Minghao Li, Lei Cui, Shaohan Huang, FuruWei, Ming Zhou, and Zhoujun Li. 2020. Tablebank: Table benchmark for image-based table detection and recognition. In Proceedings of The 12th language resources and evaluation conference. 1918--1925."},{"key":"e_1_3_2_2_19_1","volume-title":"Adaptive Scaling for Archival Table Structure Recognition. In International Conference on Document Analysis and Recognition. Springer, 80--95","author":"Li Xiao-Hui","year":"2021","unstructured":"Xiao-Hui Li , Fei Yin , Xu-Yao Zhang , and Cheng-Lin Liu . 2021 . Adaptive Scaling for Archival Table Structure Recognition. In International Conference on Document Analysis and Recognition. Springer, 80--95 . Xiao-Hui Li, Fei Yin, Xu-Yao Zhang, and Cheng-Lin Liu. 2021. Adaptive Scaling for Archival Table Structure Recognition. In International Conference on Document Analysis and Recognition. Springer, 80--95."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-68790-8_50"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.106"},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3481534"},{"key":"e_1_3_2_2_24_1","volume-title":"DAB-DETR: Dynamic anchor boxes are better queries for DETR. arXiv preprint arXiv:2201.12329","author":"Liu Shilong","year":"2022","unstructured":"Shilong Liu , Feng Li , Hao Zhang , Xiao Yang , Xianbiao Qi , Hang Su , Jun Zhu , and Lei Zhang . 2022. DAB-DETR: Dynamic anchor boxes are better queries for DETR. arXiv preprint arXiv:2201.12329 ( 2022 ). Shilong Liu, Feng Li, Hao Zhang, Xiao Yang, Xianbiao Qi, Hang Su, Jun Zhu, and Lei Zhang. 2022. DAB-DETR: Dynamic anchor boxes are better queries for DETR. arXiv preprint arXiv:2201.12329 (2022)."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00098"},{"key":"e_1_3_2_2_27_1","volume-title":"Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101","author":"Loshchilov Ilya","year":"2017","unstructured":"Ilya Loshchilov and Frank Hutter . 2017. Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101 ( 2017 ). Ilya Loshchilov and Frank Hutter. 2017. Decoupled weight decay regularization. arXiv preprint arXiv:1711.05101 (2017)."},{"key":"e_1_3_2_2_28_1","volume-title":"Robust Table Detection and Structure Recognition from Heterogeneous Document Images. arXiv preprint arXiv:2203.09056","author":"Ma Chixiang","year":"2022","unstructured":"Chixiang Ma , Weihong Lin , Lei Sun , and Qiang Huo . 2022. Robust Table Detection and Structure Recognition from Heterogeneous Document Images. arXiv preprint arXiv:2203.09056 ( 2022 ). Chixiang Ma,Weihong Lin, Lei Sun, and Qiang Huo. 2022. Robust Table Detection and Structure Recognition from Heterogeneous Document Images. arXiv preprint arXiv:2203.09056 (2022)."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00363"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.3115\/1034678.1034746"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDAR.2019.00029"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12301"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00294"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"crossref","unstructured":"Shah Rukh Qasim Hassan Mahmood and Faisal Shafait. 2019. Rethinking table recognition using graph neural networks. In ICDAR. 142--147.  Shah Rukh Qasim Hassan Mahmood and Faisal Shafait. 2019. Rethinking table recognition using graph neural networks. In ICDAR. 142--147.","DOI":"10.1109\/ICDAR.2019.00031"},{"key":"e_1_3_2_2_35_1","volume-title":"LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignment. In ICDAR.","author":"Qiao Liang","year":"2021","unstructured":"Liang Qiao , Zaisheng Li , Zhanzhan Cheng , Peng Zhang , Shiliang Pu , Yi Niu , Wenqi Ren , Wenming Tan , and Fei Wu . 2021 . LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignment. In ICDAR. Liang Qiao, Zaisheng Li, Zhanzhan Cheng, Peng Zhang, Shiliang Pu, Yi Niu, Wenqi Ren, Wenming Tan, and Fei Wu. 2021. LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignment. In ICDAR."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58604-1_5"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00260"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2019.01.008"},{"key":"e_1_3_2_2_39_1","first-page":"1162","article-title":"Deepdesrt: Deep learning for detection and structure recognition of tables in document images","volume":"1","author":"Schreiber Sebastian","year":"2017","unstructured":"Sebastian Schreiber , Stefan Agne , Ivo Wolf , Andreas Dengel , and Sheraz Ahmed . 2017 . Deepdesrt: Deep learning for detection and structure recognition of tables in document images . In ICDAR , Vol. 1. 1162 -- 1167 . Sebastian Schreiber, Stefan Agne, Ivo Wolf, Andreas Dengel, and Sheraz Ahmed. 2017. Deepdesrt: Deep learning for detection and structure recognition of tables in document images. In ICDAR, Vol. 1. 1162--1167.","journal-title":"ICDAR"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/2960811.2967152"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.89"},{"key":"e_1_3_2_2_42_1","volume-title":"Syed Tahseen Raza Rizvi","author":"Siddiqui Shoaib Ahmed","year":"2019","unstructured":"Shoaib Ahmed Siddiqui , Imran Ali Fateh , Syed Tahseen Raza Rizvi , Andreas Dengel, and Sheraz Ahmed. 2019 . DeepTabStR: deep learning based table structure recognition. In ICDAR. 1403--1409. Shoaib Ahmed Siddiqui, Imran Ali Fateh, Syed Tahseen Raza Rizvi, Andreas Dengel, and Sheraz Ahmed. 2019. DeepTabStR: deep learning based table structure recognition. In ICDAR. 1403--1409."},{"key":"e_1_3_2_2_43_1","volume-title":"Andreas Dengel","author":"Siddiqui Shoaib Ahmed","year":"2019","unstructured":"Shoaib Ahmed Siddiqui , Pervaiz Iqbal Khan , Andreas Dengel , and Sheraz Ahmed. 2019 . Rethinking semantic segmentation for table structure recognition in documents. In ICDAR. 1397--1402. Shoaib Ahmed Siddiqui, Pervaiz Iqbal Khan, Andreas Dengel, and Sheraz Ahmed. 2019. Rethinking semantic segmentation for table structure recognition in documents. In ICDAR. 1397--1402."},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00359"},{"key":"e_1_3_2_2_45_1","volume-title":"Deep Splitting and Merging for Table Structure Decomposition. In 2019 International Conference on Document Analysis and Recognition (ICDAR). 114--121","author":"Tensmeyer Chris","year":"2019","unstructured":"Chris Tensmeyer , Vlad I. Morariu , Brian Price , Scott Cohen , and Tony Martinez . 2019 . Deep Splitting and Merging for Table Structure Decomposition. In 2019 International Conference on Document Analysis and Recognition (ICDAR). 114--121 . https:\/\/doi.org\/10.1109\/ICDAR.2019.00027 Chris Tensmeyer, Vlad I. Morariu, Brian Price, Scott Cohen, and Tony Martinez. 2019. Deep Splitting and Merging for Table Structure Decomposition. In 2019 International Conference on Document Analysis and Recognition (ICDAR). 114--121. https:\/\/doi.org\/10.1109\/ICDAR.2019.00027"},{"key":"e_1_3_2_2_46_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani , Noam Shazeer , Niki Parmar , Jakob Uszkoreit , Llion Jones , Aidan N Gomez , Lukasz Kaiser , and Illia Polosukhin . 2017. Attention is all you need. Advances in neural information processing systems 30 ( 2017 ). Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_2_47_1","volume-title":"Table structure understanding and its performance evaluation. Pattern recognition 37, 7","author":"Wang Yalin","year":"2004","unstructured":"Yalin Wang , Ihsin T Phillips , and Robert M Haralick . 2004. Table structure understanding and its performance evaluation. Pattern recognition 37, 7 ( 2004 ), 1479--1497. Yalin Wang, Ihsin T Phillips, and Robert M Haralick. 2004. Table structure understanding and its performance evaluation. Pattern recognition 37, 7 (2004), 1479--1497."},{"key":"e_1_3_2_2_48_1","volume-title":"Anchor detr: Query design for transformer-based detector. arXiv preprint arXiv:2109.07107","author":"Wang Yingming","year":"2021","unstructured":"Yingming Wang , Xiangyu Zhang , Tong Yang , and Jian Sun . 2021. Anchor detr: Query design for transformer-based detector. arXiv preprint arXiv:2109.07107 ( 2021 ). Yingming Wang, Xiangyu Zhang, Tong Yang, and Jian Sun. 2021. Anchor detr: Query design for transformer-based detector. arXiv preprint arXiv:2109.07107 (2021)."},{"key":"e_1_3_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDAR.2019.00125"},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00133"},{"key":"e_1_3_2_2_51_1","volume-title":"Efficient detr: improving end-to-end object detector with dense prior. arXiv preprint arXiv:2104.01318","author":"Yao Zhuyu","year":"2021","unstructured":"Zhuyu Yao , Jiangbo Ai , Boxun Li , and Chi Zhang . 2021. Efficient detr: improving end-to-end object detector with dense prior. arXiv preprint arXiv:2104.01318 ( 2021 ). Zhuyu Yao, Jiangbo Ai, Boxun Li, and Chi Zhang. 2021. Efficient detr: improving end-to-end object detector with dense prior. arXiv preprint arXiv:2104.01318 (2021)."},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.555"},{"key":"e_1_3_2_2_53_1","volume-title":"embed and merge: An accurate table structure recognizer. Pattern Recognition","author":"Zhang Zhenrong","year":"2022","unstructured":"Zhenrong Zhang , Jianshu Zhang , Jun Du , and Fengren Wang . 2022. Split , embed and merge: An accurate table structure recognizer. Pattern Recognition ( 2022 ), 108565. Zhenrong Zhang, Jianshu Zhang, Jun Du, and Fengren Wang. 2022. Split, embed and merge: An accurate table structure recognizer. Pattern Recognition (2022), 108565."},{"key":"e_1_3_2_2_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00074"},{"key":"e_1_3_2_2_55_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58589-1_34"},{"key":"e_1_3_2_2_56_1","volume-title":"International Conference on Learning Representations.","author":"Zhu Xizhou","year":"2021","unstructured":"Xizhou Zhu , Weijie Su , Lewei Lu , Bin Li , Xiaogang Wang , and Jifeng Dai . 2021 . Deformable detr: Deformable transformers for end-to-end object detection . In International Conference on Learning Representations. Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai. 2021. Deformable detr: Deformable transformers for end-to-end object detection. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSP48669.2020.9321003"}],"event":{"name":"MM '22: The 30th ACM International Conference on Multimedia","location":"Lisboa Portugal","acronym":"MM '22","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 30th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3503161.3548038","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3503161.3548038","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:02:29Z","timestamp":1750186949000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3503161.3548038"}},"subtitle":["Table Structure Recognition with Transformers"],"short-title":[],"issued":{"date-parts":[[2022,10,10]]},"references-count":57,"alternative-id":["10.1145\/3503161.3548038","10.1145\/3503161"],"URL":"https:\/\/doi.org\/10.1145\/3503161.3548038","relation":{},"subject":[],"published":{"date-parts":[[2022,10,10]]},"assertion":[{"value":"2022-10-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}