--
-- Host: localhost    Database: scanrefer_benchmark
-- ------------------------------------------------------


--
-- Table structure for table `localization_results`
--

CREATE TABLE `localization_results` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `submission_id` int(11) DEFAULT NULL,
  `unique_acc_0_25IoU` float DEFAULT NULL,
  `unique_acc_0_5IoU` float DEFAULT NULL,
  `multiple_acc_0_25IoU` float DEFAULT NULL,
  `multiple_acc_0_5IoU` float DEFAULT NULL,
  `overall_acc_0_25IoU` float DEFAULT NULL,
  `overall_acc_0_5IoU` float DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=71 DEFAULT CHARSET=latin1;

--
-- Dumping data for table `localization_results`
--

INSERT INTO `localization_results` VALUES (0,0,0.629,0.4031,0.3088,0.1654,0.3806,0.2187),(13,9,0.685903,0.435284,0.348821,0.209674,0.424399,0.260259),(14,8,0.685903,0.435284,0.348821,0.209674,0.424399,0.260259),(15,11,0.685903,0.435284,0.348821,0.209674,0.424399,0.260259),(16,10,0,0,0,0,0,0),(17,12,0.66859,0.551525,0.330712,0.253514,0.406469,0.320333),(20,15,0.68343,0.589448,0.331189,0.252561,0.410166,0.328096),(21,16,0.624073,0.533388,0.281868,0.213009,0.358595,0.284843),(26,19,0.642209,0.419621,0.30903,0.183226,0.383734,0.236229),(28,20,0.727123,0.62737,0.318799,0.246605,0.410351,0.331978),(30,17,0.74526,0.637263,0.348821,0.268525,0.437708,0.351201),(32,21,0.753504,0.641385,0.345723,0.265666,0.437153,0.349908),(33,22,0.752679,0.636439,0.351442,0.271146,0.441405,0.35305),(35,24,0.752679,0.643034,0.346676,0.270193,0.437708,0.353789),(36,13,0.747733,0.639736,0.340958,0.266619,0.432163,0.350277),(37,14,0.752679,0.644683,0.33929,0.258518,0.431978,0.345102),(38,18,0.752679,0.644683,0.33929,0.258518,0.431978,0.345102),(39,25,0.752679,0.644683,0.33929,0.258518,0.431978,0.345102),(40,27,0.7494,0.5128,0.3631,0.2218,0.4497,0.2871),(42,31,0.757626,0.551525,0.422445,0.293305,0.497597,0.351201),(44,33,0.751031,0.639736,0.327138,0.253514,0.422181,0.340111),(45,23,0.778236,0.666941,0.345723,0.268763,0.442699,0.358041),(46,30,0.773289,0.57873,0.436979,0.310222,0.512384,0.370425),(47,34,0.577906,0.360264,0.279247,0.174649,0.346211,0.216266),(48,35,0.701566,0.520198,0.323326,0.195854,0.408133,0.268577),(50,37,0.600989,0.465787,0.253991,0.172981,0.331793,0.238632),(51,38,0.600989,0.465787,0.253991,0.172981,0.331793,0.238632),(52,39,0.76587,0.657873,0.361925,0.272576,0.452495,0.358965),(54,32,0.767519,0.605936,0.438885,0.311651,0.512569,0.377634),(55,41,0.783182,0.680132,0.385037,0.294734,0.474307,0.381146),(63,40,0.792251,0.684254,0.390517,0.307362,0.480592,0.391867),(64,52,0.750206,0.597692,0.371218,0.262807,0.456192,0.337893),(65,53,0.773289,0.680956,0.361925,0.291875,0.454159,0.379113),(66,54,0.776587,0.684254,0.361687,0.290446,0.454713,0.378743),(67,51,0.785655,0.58615,0.431737,0.293543,0.511091,0.35915),(69,56,0.784831,0.549876,0.393376,0.248034,0.481146,0.315712),(70,57,0.769167,0.588623,0.414105,0.292352,0.493715,0.35878);

--
-- Table structure for table `captioning_results`
--

CREATE TABLE `captioning_results` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `submission_id` int(11) DEFAULT NULL,
  `cider_0_5IoU` float DEFAULT NULL,
  `bleu_4_0_5IoU` float DEFAULT NULL,
  `rouge_0_5IoU` float DEFAULT NULL,
  `meteor_0_5IoU` float DEFAULT NULL,
  `DCmAP` float DEFAULT NULL,
  `mAP_0_5` float DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=71 DEFAULT CHARSET=latin1;

--
-- Dumping data for table `captioning_results`
--

-- INSERT INTO `captioning_results` VALUES (0,8,0.0849,0.0576,0.1073,0.0492,0.0970,0.2481);

--
-- Table structure for table `maintainers`
--

CREATE TABLE `maintainers` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `name` varchar(255) DEFAULT NULL,
  `email` varchar(255) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1;

--
-- Dumping data for table `maintainers`
--


--
-- Table structure for table `submissions`
--

CREATE TABLE `submissions` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `upload_folder_random` varchar(225) NOT NULL,
  `short_name` varchar(20) NOT NULL,
  `full_name` varchar(80) NOT NULL,
  `description` varchar(1000) NOT NULL,
  `task_type` tinyint(1) NOT NULL,
  `publication_title` varchar(400) NOT NULL,
  `publication_authors` varchar(400) NOT NULL,
  `publication_venue` varchar(200) NOT NULL,
  `publication_url` varchar(200) NOT NULL,
  `languages` varchar(200) NOT NULL,
  `hardware` varchar(200) NOT NULL,
  `website_url` varchar(200) NOT NULL,
  `source_url` varchar(200) NOT NULL,
  `availability` tinyint(1) NOT NULL,
  `anonymous` tinyint(1) NOT NULL,
  `status` tinyint(1) NOT NULL,
  `published` tinyint(1) NOT NULL,
  `creation_stamp` bigint(20) NOT NULL,
  `last_upload_number` int(11) NOT NULL,
  `last_upload_stamp` bigint(20) NOT NULL,
  `last_test_set_upload_stamp` bigint(20) NOT NULL,
  `submitted_by_user_id` int(11) NOT NULL,
  `last_change_stamp` bigint(20) NOT NULL,
  `uses_xyz` tinyint(1) NOT NULL,
  `uses_rgb` tinyint(1) NOT NULL,
  `uses_multiview` tinyint(1) NOT NULL,
  `uses_normal` tinyint(1) NOT NULL,
  `ip` varchar(50) NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=58 DEFAULT CHARSET=latin1;

--
-- Dumping data for table `submissions`
--

INSERT INTO `submissions` VALUES (8,'eaa4d58c4515c78dd1c00d662e3ac894','ScanRefer','VoteNet + GRU (end-to-end)','VoteNet + GRU-based localization module trained in end-to-end fashine on ScanRefer dataset.',1,'ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language','Dave Zhenyu Chen, Angel X. Chang, Matthias Nießner','16th European Conference on Computer Vision (ECCV), 2020','https://arxiv.org/pdf/1912.08830','Python','GeForce 2080Ti','https://daveredrum.github.io/ScanRefer/','https://daveredrum.github.io/ScanRefer/',3,0,3,1,1596011547,2,1597237185,1597237185,0,1596011547,1,0,1,1,'131.159.40.127'),(15,'be724681ef3ed1ac66492bb560b0301b','TGNN','Text guided graph neural network','',1,'Text-Guided Graph Neural Network for Referring 3D Instance Segmentation','Pin-Hao Huang, Han-Hung Lee, Hwann-Tzong Chen, Tyng-Luh Liu','AAAI 2021','https://www.aaai.org/AAAI21Papers/AAAI-4433.HuangP.pdf','Python','nvidia 1080ti','','',0,0,3,1,1599458838,1,1599458859,1599458859,11,1612555322,1,1,0,0,'223.137.133.190'),(19,'5314413d23243e9c668cbe4117922aa2','ScanRefer Baseline','ScanRefer Baseline','',1,'','','','','python','tesla 1080T','','',0,1,3,0,1604380328,1,1604381238,1604381238,14,1604380328,1,1,0,0,'124.126.230.100'),(23,'89113b8053f08b65bc664157a21836fa','InstanceRefer','InstanceRefer','',1,'InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referring','Zhihao Yuan, Xu Yan, Yinghong Liao, Ruimao Zhang, Zhen Li*, Shuguang Cui','ICCV 2021','https://arxiv.org/pdf/2103.01128.pdf','Python','V100','','https://github.com/CurryYuan/InstanceRefer',3,0,3,0,1605686587,2,1615964651,1615964651,12,1627531312,1,1,0,0,'203.184.132.206'),(26,'a161fa0178043e301b063fbeb09272a6','Test Submission','Test Submission','Test Submission',1,'Test Submission','Test Submission','Test Submission','','Test Submission','Test Submission','','',0,0,0,0,1612804847,0,0,0,0,1612804847,1,0,0,0,'2.205.2.75'),(27,'66ec0e01dad55b103bc50bd4947b635e','SRGA','ScanRefer with Convolutional Graph NN and Language Self-Attention','ScanRefer with a graph neural network and a language self-attention mechanism to improve the understanding of relationships between objects within a scene.',1,'','','','','Python','GTX1060 6GB, Colab, RTX2080TI uni server','https://github.com/DomiSchmauser/ScanRefer-with-Graph-and-Attention-SRGA/blob/main/docs/SRGA.pdf','',0,0,3,0,1612805164,1,1612809323,1612809323,16,1616141946,1,0,1,1,'93.192.57.121'),(28,'87e882567634b648d92fce3037f2815f','ScanNotRefer','NoGRU','Nothing',1,'NoPublication','','','','NoLanguage','NoHW','','',0,0,4,0,1612807023,1,1612807049,0,17,1612807023,1,0,1,1,'96.48.224.214'),(29,'b1c84ca9e59354cdb087e3868484b291','BigMoodNet','BIGMOODNET','Big + Mood + Neural Nets = Profit',1,'Mood is all you need','Onishi San','BIGCV','','C++ CUDA','4099Ti','','',0,0,4,0,1612808092,1,1612808229,0,18,1612808092,1,1,0,0,'84.138.83.245'),(30,'4e9e2f945545a70d5c88540771f17cef','3DVG-Trans +','An *extension* for 3DVG-Transformer','trained on an end-to-end version\r\nA simple extension for 3DVG-Transformer\r\n(Not placed in the body of the ICCV paper)',1,'3DVG-Transformer: Relation Modeling for Visual Grounding on Point Clouds','Lichen Zhao∗, Daigang Cai∗, Lu Sheng†, Dong Xu','ICCV2021','','Python','GeForce RTX 2080 Ti, 11GB RAM','','https://github.com/zlccccc/3DVG-Transformer',3,0,3,0,1614072876,3,1616684765,1616684765,19,1650168323,1,0,1,1,'123.126.82.6'),(31,'2364732f78a012182162ecd7735775d9','3DVG-Transformer','3DVG-Transformer: Relation Modeling for Visual Grounding on Point Clouds','',1,'3DVG-Transformer: Relation Modeling for Visual Grounding on Point Clouds','Lichen Zhao∗, Daigang Cai∗, Lu Sheng†, Dong Xu','ICCV2021','https://openaccess.thecvf.com/content/ICCV2021/papers/Zhao_3DVG-Transformer_Relation_Modeling_for_Visual_Grounding_on_Point_Clouds_ICCV_2021_paper.pdf','Python With Cuda','GeForce RTX 2080 Ti, 11GB RAM','','https://github.com/zlccccc/3DVG-Transformer',3,0,3,0,1615012406,1,1615015941,1615015941,19,1650168320,1,0,1,1,'123.126.82.6'),(32,'fb296894ec03611739b30c9bedac0e8f','3DJCG','3DJCG','Joint Training\r\nWe use the VoteNet backbone for detection.',1,'3DJCG: A Unified Framework for Joint Dense Captioning and Visual Grounding on 3D Point Clouds','Daigang Cai, Lichen Zhao, Jing Zhang†, Lu Sheng, Dong Xu','CVPR2022 Oral','https://openaccess.thecvf.com/content/CVPR2022/papers/Cai_3DJCG_A_Unified_Framework_for_Joint_Dense_Captioning_and_Visual_CVPR_2022_paper.pdf','Python With Cuda','GeForce RTX 2080 Ti, 11GB RAM','','https://github.com/zlccccc/3DJCG',3,0,3,0,1615024701,1,1635860775,1635860775,20,1658997667,1,0,1,1,'119.3.119.19'),(33,'41a3e4c83880ea10a91baa158af225c3','PointGroup_MCAN','PointGroup_MCAN','',1,'','','','','Pytorch with CUDA10.1','RTX 2080','','',0,1,3,0,1615960271,1,1615960319,1615960319,21,1615960271,1,1,0,0,'58.250.174.78'),(34,'a0117176564198858e4bae331d39a999','pairwisemethod','pairwisemethod','',1,'','','','','python','GeForce RTX 2080 Ti','','',0,1,3,0,1617082767,1,1617259870,1617259870,22,1617082767,1,1,0,0,'202.120.46.22'),(35,'5e29cc53e67583d36c796a4cf7d9b5b4','SR-GAB','ScanRefer + BRNet + DGCNN + Self-Attention + Cross-modal Attention (end-to-end)','Uses BRNet for object detection, self-attention for language embeddings, cross-modal attention for visual and textual embeddings, apply DGCNN to fused features',1,'','','','','Python','GeForce RTX 2080 Ti','','https://github.com/yoonhachoe/ScanRefer-GAB',0,0,3,0,1625759158,1,1625759385,1625759385,25,1626354114,1,0,1,1,'5.26.190.198'),(38,'aff8d4550653a93d12ae41c342a4cc77','TransformerRefer','ScanRefer with Transformer-based Object Detection','ScanRefer method, but replaced VoteNet with Group-Free Transformer-based 3D Object Detector.\r\nUses their provided weights for the 12 layer, double width, 256 candidates model as initialization, and therefor only XYZ (without height) as input features.',1,'','','','','Python','GeForce RTX 2080 Ti, 11GB RAM','','',0,0,3,0,1625780115,1,1625780120,1625780120,24,1625780115,1,0,0,0,'2.206.9.239'),(39,'56b495e0ff30f846e468927bfc14e807','D3Net - Pretrained','PointGroup + Transformer (w/o end-to-end fine-tuning)','This is the pretrained version of D3Net - PointGroup + Transformer (w/o end-to-end fine-tuning)',1,'D3Net: A Unified Speaker-Listener Architecture for 3D Dense Captioning and Visual Grounding','Dave Zhenyu Chen, Qirui Wu, Matthias Niessner, Angel X. Chang','17th European Conference on Computer Vision (ECCV), 2022','https://arxiv.org/abs/2112.01551','Python','RTX 3090Ti','https://daveredrum.github.io/D3Net/','https://github.com/daveredrum/D3Net',3,0,4,0,1635326122,1,1635326265,1635326265,0,1658574818,1,0,1,1,'2.206.9.109'),(40,'b39d9d504d606774b52f798018e27a57','D3Net','PointGroup + Transformer (w/ end-to-end fine-tuning)','This is the final version of D3Net - PointGroup + Transformer (w/ end-to-end fine-tuning)',1,'D3Net: A Unified Speaker-Listener Architecture for 3D Dense Captioning and Visual Grounding','Dave Zhenyu Chen, Qirui Wu, Matthias Niessner, Angel X. Chang','17th European Conference on Computer Vision (ECCV), 2022','https://arxiv.org/abs/2112.01551','Python','RTX 3090Ti','https://daveredrum.github.io/D3Net/','https://github.com/daveredrum/D3Net',3,0,3,0,1635326769,2,1636646918,1636646918,0,1658574810,1,0,1,1,'2.206.9.109'),(41,'4afc58650cfb7640b646e849e4bf7b19','ContraRefer','PointGroup + GRU (w/o end-to-end fine-tuning)','',1,'','','','','Python','GeForce RTX 2080 Ti','','',0,1,3,0,1636184078,1,1636184483,1636184483,28,1637167127,1,1,0,1,'119.78.254.4'),(42,'ac7809072cde9205998e6d789f512adb','testRefer1','testRefer1','test refer',1,'','','','','python','GeForce RTX 2080 Ti','','',3,1,3,0,1636446310,1,1636446446,1636446446,30,1636446310,1,1,0,1,'106.39.42.243'),(43,'da62ead440bafea7e5d1d55c45e976df','refertrans','refer+transformer','',1,'','','','','python','GeForce RTX 2080 Ti','','',0,1,3,0,1636453867,1,1636453891,1636453891,30,1636456733,1,1,0,1,'106.39.42.243'),(47,'b2f77638ecb7e335955141eff0be0889','3DGNN','3DGNN','',1,'','','','','python','RTX 1080','','',0,1,3,0,1636550504,1,1636550785,1636550785,32,1636550504,1,1,0,1,'103.37.140.35'),(51,'229e031d6bdd9b05a0aa13a1e1ccafe4','FE-3DGQA','Anonymous','Ground Multiple Object!',1,'','','','','Python With Cuda','NVIDIA V100','','',0,1,3,0,1636979687,1,1646906065,1646906065,20,1646968378,1,0,1,1,'106.39.42.113'),(52,'55226427a2c61d1a40ecf4905ef8c14a','TransformerVG','3DETR+3DVG+GRU','3DETR-M + 3DVG + GRU without end-to-end training. 3DETR-m is pre-trained and then fine tuned.',1,'','','','','python','Nvidia GeForce RTX 3080ti, 3090ti and 2080ti','https://github.com/ChenBarryHu/TransformerVG','https://github.com/ChenBarryHu/TransformerVG',0,0,4,0,1643562180,1,1643904103,1643904103,26,1643904291,1,0,1,1,'93.202.63.217'),(53,'c2aa3ca22f23d778df05e6900e45897d','Clip','PointGroup + GRU','',1,'','','','','Python','GeForce RTX 2080 Ti','','',0,1,4,0,1646593487,1,1646594740,1646594740,28,1646595783,1,1,0,1,'27.122.59.204'),(54,'a08c87c5f3bf32f753c8596d5150bf7a','Clip-pre','PointGroup + GRU','',1,'','','','','Python','GeForce RTX 2080 Ti','','',0,1,3,0,1646597390,1,1646598011,1646598011,28,1646597390,1,1,0,1,'27.122.59.204'),(56,'a3e621cef4570d136f7d32f535c458ab','BEAUTY-DETR','BEAUTY-DETR','DETR-based architecture with iterative bottom-up and top-down attention on language, boxes and point features. Decodes boxes instead of selecting from a pool of proposals.',1,'Looking Outside the Box to Ground Language in 3D Scenes','Ayush Jain, Nikolaos Gkanatsios, Ishita Mediratta, Katerina Fragkiadaki','','https://arxiv.org/abs/2112.08879','Python','NVIDIA-A100','','https://github.com/nickgkan/beauty_detr',2,0,3,0,1649862393,1,1649862416,1649862416,35,1649862393,1,1,0,0,'128.237.82.12'),(57,'6f72e46cfd6009fabab251027e2ccaa0','HGT','PointGroup + GRU (end to end)','',1,'','','','','Python with CUDA','Geforce 3090, 24GB RAM','','',0,1,3,0,1652275971,1,1652278939,1652278939,36,1652275971,1,0,1,1,'103.72.5.101');

--
-- Table structure for table `uc_configuration`
--

CREATE TABLE `uc_configuration` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `name` varchar(150) NOT NULL,
  `value` varchar(150) NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=8 DEFAULT CHARSET=utf8;

--
-- Dumping data for table `uc_configuration`
--

INSERT INTO `uc_configuration` VALUES (1,'website_name','ScanRefer Benchmark'),(2,'website_url','kaldir.vc.in.tum.de/scanrefer_benchmark'),(3,'email','noreplyscanrefer@gmail.com'),(4,'activation','false'),(5,'resend_activation_threshold','0'),(6,'language','models/languages/en.php'),(7,'template','models/site-templates/default.css');

--
-- Table structure for table `uc_pages`
--

CREATE TABLE `uc_pages` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `page` varchar(150) NOT NULL,
  `private` tinyint(1) NOT NULL DEFAULT '0',
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1;

--
-- Dumping data for table `uc_pages`
--


--
-- Table structure for table `uc_permission_page_matches`
--

CREATE TABLE `uc_permission_page_matches` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `permission_id` int(11) NOT NULL,
  `page_id` int(11) NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1;

--
-- Dumping data for table `uc_permission_page_matches`
--


--
-- Table structure for table `uc_permissions`
--

CREATE TABLE `uc_permissions` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `name` varchar(150) NOT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

--
-- Dumping data for table `uc_permissions`
--


--
-- Table structure for table `uc_user_permission_matches`
--

CREATE TABLE `uc_user_permission_matches` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
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  PRIMARY KEY (`id`)
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--
-- Dumping data for table `uc_user_permission_matches`
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INSERT INTO `uc_user_permission_matches` VALUES (16,9,1),(17,10,1),(18,11,1),(19,12,1),(20,13,1),(21,14,1),(22,15,1),(23,16,1),(24,17,1),(25,18,1),(26,19,1),(27,20,1),(28,21,1),(29,22,1),(30,23,1),(31,24,1),(32,25,1),(33,26,1),(34,27,1),(35,28,1),(36,29,1),(37,30,1),(38,31,1),(39,32,1),(40,33,1),(41,34,1),(42,35,1),(43,36,1),(44,37,1);

--
-- Table structure for table `uc_users`
--

CREATE TABLE `uc_users` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `user_name` varchar(50) NOT NULL,
  `password` varchar(225) NOT NULL,
  `email` varchar(150) NOT NULL,
  `website` varchar(200) NOT NULL,
  `first_name` varchar(50) NOT NULL,
  `last_name` varchar(50) NOT NULL,
  `newsletter_subscribed` tinyint(1) NOT NULL,
  `activation_token` varchar(225) NOT NULL,
  `last_activation_request` int(11) NOT NULL,
  `lost_password_request` tinyint(1) NOT NULL,
  `active` tinyint(1) NOT NULL,
  `title` varchar(150) NOT NULL,
  `sign_up_stamp` bigint(20) NOT NULL,
  `last_sign_in_stamp` bigint(20) NOT NULL,
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--
-- Dumping data for table `uc_users`
--

INSERT INTO `uc_users` VALUES (0,'scanrefer','0fae6d75a438bfd2876e635bc8f8c026bd4f996d996fec94d129dad3e11b159c7','zhenyu.chen@tum.de','https://www.niessnerlab.org/members/zhenyu_chen/profile.html','Dave Zhenyu','Chen',0,'38c58047ca353b2580beebe726e092dd',1552480510,0,1,'New Member',1552480510,1658571260,'::1'),(11,'haohao','5a5f8f32593d8e6df82f4c51223574e3f7abb15fbdf60a32163b060b0562b54fc','godhuang12345678@iis.sinica.edu.tw','','Pin-Hao','Huang',0,'2c7ccf3fb6bf0daaceca2ba7141998e1',1596169898,0,1,'New Member',1596169898,1612553885,'140.109.19.241'),(12,'curryyuan','a869b66fefec9ab43199ed28a08d7d7400c3be7287f4fb3b39f9cbf3832adf1f7','yuanzhh5@mail2.sysu.edu.cn','','Zhihao','Yuan',0,'3c52a53747dd3e9c3ecb4e6f4a941417',1596368328,0,1,'New Member',1596368328,1627531256,'45.135.48.12'),(13,'rexleeppp','86830c5f3ea483f6a03235bb1cb4c1fae49547cec6a6add2b1da2c8ef0d33c044','rexleeppp@gmail.com','','Han-Hung','Lee',0,'fb44fef7e41d5773a4c634fb052004e5',1598441331,0,1,'New 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