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<title>Download – Cityscapes Dataset</title> |
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<style>img:is([sizes="auto" i], [sizes^="auto," i]) { contain-intrinsic-size: 3000px 1500px }</style> |
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</style> |
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<link rel='stylesheet' id='collapscore-css-css' href='https://www.cityscapes-dataset.com/wordpress/wp-content/plugins/jquery-collapse-o-matic/css/core_style.css?ver=1.0' type='text/css' media='all' /> |
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<link rel='stylesheet' id='collapseomatic-css-css' href='https://www.cityscapes-dataset.com/wordpress/wp-content/plugins/jquery-collapse-o-matic/css/light_style.css?ver=1.6' type='text/css' media='all' /> |
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<link rel='stylesheet' id='datatables-css' href='https://cdn.datatables.net/v/dt/dt-2.2.1/b-3.2.0/b-html5-3.2.0/b-print-3.2.0/fc-5.0.4/datatables.min.css?ver=6.7.1' type='text/css' media='all' /> |
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font-weight : inherit;
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body,.navbar .nav>li>a {
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font-family : 'Verdana','Geneva','sans-serif';
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font-weight : inherit;
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body,.navbar .nav>li>a {
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line-height : 1.6em;
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} |
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</style> |
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<link rel='stylesheet' id='customizr-style-css' href='https://www.cityscapes-dataset.com/wordpress/wp-content/themes/cityscapes-theme/style.css?ver=4.4.24' type='text/css' media='all' /> |
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<link rel='stylesheet' id='video-js-css' href='https://www.cityscapes-dataset.com/wordpress/wp-content/plugins/video-embed-thumbnail-generator/video-js/video-js.min.css?ver=7.17.0' type='text/css' media='all' /> |
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<link rel='stylesheet' id='video-js-kg-skin-css' href='https://www.cityscapes-dataset.com/wordpress/wp-content/plugins/video-embed-thumbnail-generator/video-js/kg-video-js-skin.css?ver=4.10.2' type='text/css' media='all' /> |
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<link rel='stylesheet' id='kgvid_video_styles-css' href='https://www.cityscapes-dataset.com/wordpress/wp-content/plugins/video-embed-thumbnail-generator/src/public/css/videopack-styles.css?ver=4.10.2' type='text/css' media='all' /> |
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<link rel="https://api.w.org/" href="https://www.cityscapes-dataset.com/wp-json/" /><link rel="alternate" title="JSON" type="application/json" href="https://www.cityscapes-dataset.com/wp-json/wp/v2/pages/370" /><link rel="EditURI" type="application/rsd+xml" title="RSD" href="https://www.cityscapes-dataset.com/wordpress/xmlrpc.php?rsd" /> |
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<a class="site-logo" href="https://www.cityscapes-dataset.com/" aria-label="Cityscapes Dataset | Semantic Understanding of Urban Street Scenes"><img src="https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2015/07/cityscapesLogo.png" alt="Back Home" width="1999" height="369" style="max-width:250px;max-height:100px" data-no-retina class=" attachment-289"/></a> </div>
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<div class="container outside"><h2 class="site-description">Semantic Understanding of Urban Street Scenes</h2></div> <div class="navbar-wrapper clearfix span9 tc-submenu-fade tc-submenu-move tc-open-on-hover pull-menu-right">
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<h2 class="span7 inside site-description">Semantic Understanding of Urban Street Scenes</h2><div class="nav-collapse collapse tc-hover-menu-wrapper"><div class="menu-main-menu-container"><ul id="menu-main-menu-2" class="nav tc-hover-menu"><li class="menu-item menu-item-type-post_type menu-item-object-page menu-item-228"><a href="https://www.cityscapes-dataset.com/news/">News</a></li> |
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<h1 class="entry-title ">Download</h1><hr class="featurette-divider __before_content"> </header>
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<p>Below, you can find all currently available downloads. A README and various scripts for inspection, preparation, and evaluation can be found in our <a href="https://github.com/mcordts/cityscapesScripts" target="_blank" rel="noopener noreferrer">git repository</a>.</p> |
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#csPackageList ul { list-style-type: none; font-style:italic; font-size:18px; color:#999; } |
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#csPackageList ul li { height: 100px; } |
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#csPackageList ul li p { padding:5px; padding-left:8px; font-style:normal; font-size:16px; color:#444; border-left: 1px solid #999; height: 80px; } |
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<div id='csPackageCategory'><h4>The following packages are available for download. Please download only those packages that you need for your immediate research.</h4><div id='csPackageList'><ul ><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/jena00_small.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=1'>gtFine_trainvaltest.zip (241MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=1' target='_blank'>[md5]</a></em> fine annotations for train and val sets (3475 annotated images) and dummy annotations (ignore regions) for the test set (1525 images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/erlangen00_small.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=2'>gtCoarse.zip (1.3GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=2' target='_blank'>[md5]</a></em> coarse annotations for train and val set (3475 annotated images) and train_extra (19998 annotated images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_img_small.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=3'>leftImg8bit_trainvaltest.zip (11GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=3' target='_blank'>[md5]</a></em> left 8-bit images - train, val, and test sets (5000 images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_img_small.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=4'>leftImg8bit_trainextra.zip (44GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=4' target='_blank'>[md5]</a></em> left 8-bit images - trainextra set (19998 images, note that the image "troisdorf_000000_000073_leftImg8bit.png" is corrupt/black)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_img_small_stereo.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=5'>rightImg8bit_trainvaltest.zip (11GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=5' target='_blank'>[md5]</a></em> right 8-bit images - train, val, and test sets (5000 images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_img_small_stereo.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=6'>rightImg8bit_trainextra.zip (44GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=6' target='_blank'>[md5]</a></em> right 8-bit images - trainextra set (19998 images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_depth150.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=7'>disparity_trainvaltest.zip (3.5GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=7' target='_blank'>[md5]</a></em> precomputed depth maps using SGM for train, val, and test sets (5000 images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_depth150.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=22'>disparity_trainextra.zip (15GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=22' target='_blank'>[md5]</a></em> precomputed depth maps using SGM for trainextra set</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/cameraDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=8'>camera_trainvaltest.zip (2MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=8' target='_blank'>[md5]</a></em> intrinsic and extrinsic camera parameters for train, val, and test sets</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/cameraDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=9'>camera_trainextra.zip (8MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=9' target='_blank'>[md5]</a></em> intrinsic and extrinsic camera parameters for trainextra set</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/vehicleDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=10'>vehicle_trainvaltest.zip (2MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=10' target='_blank'>[md5]</a></em> vehicle odometry + GPS coordinates + temperature for train, val, and test sets</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/vehicleDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=11'>vehicle_trainextra.zip (7MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=11' target='_blank'>[md5]</a></em> vehicle odometry + GPS coordinates + temperature for trainextra set</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/03/demoVideoDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=12'>leftImg8bit_demoVideo.zip (6.6GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=12' target='_blank'>[md5]</a></em> video sequences for qualitative evaluation, left 8-bit images only</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/03/demoVideoDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=13'>all_demoVideo.zip (59GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=13' target='_blank'>[md5]</a></em> video sequences for qualitative evaluation, all types of data</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2019/01/downloadblurred.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=32'>leftImg8bit_blurred.zip (11GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=32' target='_blank'>[md5]</a></em> Left 8-bit images with blurred faces and license plates. Please compute results on the original images but use the blurred ones for visualization. We thank <a href="https://www.mapillary.com" target="_blank">Mapillary</a> for blurring the images.</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_img_small.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=14'>leftImg8bit_sequence_trainvaltest.zip (324GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=14' target='_blank'>[md5]</a></em> 30-frame snippets (17Hz) surrounding each left 8-bit image (-19 | +10) from the train, val, and test sets (150000 images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/03/timestampDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=21'>timestamp_sequence.zip (40MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=21' target='_blank'>[md5]</a></em> timestamps for 30-frame snippets from train, val, and test sets</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/vehicleDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=20'>vehicle_sequence.zip (56MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=20' target='_blank'>[md5]</a></em> vehicle odometry + GPS coordinates + temperature for 30-frame snippets from train, val, and test sets</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_img_small_stereo.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=15'>rightImg8bit_sequence_trainvaltest.zip (322GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=15' target='_blank'>[md5]</a></em> 30-frame snippets (17Hz) surrounding each right 8-bit image (-19 | +10) from the train, val, and test sets (150000 images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_depth150.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=26'>disparity_sequence_trainvaltest.zip (106GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=26' target='_blank'>[md5]</a></em> precomputed depth maps using SGM for 30-frame snippets from train, val, and test sets</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_img_small.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=23'>leftImg8bit_allFrames_frankfurt.zip (241GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=23' target='_blank'>[md5]</a></em> left 8-bit images for whole drive in frankfurt from val set</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/03/timestampDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=24'>timestamp_allFrames_frankfurt.zip (29MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=24' target='_blank'>[md5]</a></em> timestamps for whole drive in frankfurt from val set</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/vehicleDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=25'>vehicle_allFrames_frankfurt.zip (38MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=25' target='_blank'>[md5]</a></em> vehicle odometry + GPS coordinates + temperature for whole drive in frankfurt from val set</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/03/hdrLeftDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=16'>leftImg16bit_trainvaltest.zip (37GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=16' target='_blank'>[md5]</a></em> left HDR images stored as 16-bit PNGs - train, val, and test sets (5000 images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/02/berlin00056_img_small_stereo.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=27'>rightImg8bit_allFrames_frankfurt.zip (242GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=27' target='_blank'>[md5]</a></em> right 8-bit images for whole drive in frankfurt from val set</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/03/hdrLeftDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=17'>leftImg16bit_trainextra.zip (149GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=17' target='_blank'>[md5]</a></em> left HDR images stored as 16-bit PNGs - trainextra set (19998 images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/03/hdrRightDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=18'>rightImg16bit_trainvaltest.zip (37GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=18' target='_blank'>[md5]</a></em> right HDR images stored as 16-bit PNGs - train, val, and test sets (5000 images)</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2016/03/hdrRightDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=19'>rightImg16bit_trainextra.zip (149GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=19' target='_blank'>[md5]</a></em> right HDR images stored as 16-bit PNGs - trainextra set (19998 images)</p></li></ul></div></div> |
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<div id='csPackageCategory'><hr><h4>The following packages from third party publications are available for download.</h4><p>If you use the packages in your research, please cite both publications, <a href='https://www.cityscapes-dataset.com/citation/'>Cityscapes</a> and the work listed in conjunction with the package. Please contact the respective authors directly in case of questions.</p><div id='csPackageList'><ul ><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2020/06/3dboxesDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=34'>gtBbox3d_trainvaltest.zip (6.6MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=34' target='_blank'>[md5]</a></em> 3D bounding box annotations of vehicles for train and val sets (3475 annotated images). Citation: N. Gählert, N. Jourdan, M. Cordts, U. Franke, and J. Denzler, <a href="https://arxiv.org/abs/2006.07864" target="_blank">"Cityscapes 3D: Dataset and Benchmark for 9 DoF Vehicle Detection"</a>, CVPRW 2020.</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2017/08/citypersonsDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=28'>gtBbox_cityPersons_trainval.zip (2.2MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=28' target='_blank'>[md5]</a></em> CityPersons bounding box annotations of people for train and val sets (3475 annotated images). Citation: S. Zhang, R. Benenson, and B. Schiele, <a href="http://openaccess.thecvf.com/content_cvpr_2017/html/Zhang_CityPersons_A_Diverse_CVPR_2017_paper.html" target="_blank">"CityPersons: A Diverse Dataset for Pedestrian Detection"</a>, CVPR 2017.</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2021/01/panopticPartsDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=35'>gtFinePanopticParts_trainval.zip (474MB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=35' target='_blank'>[md5]</a></em> Panoptic parts annotations for train and val sets (3475 annotated images). Citation: P. Meletis, X. Wen, C. Lu, D. de Geus, and G. Dubbelman, <a href="https://arxiv.org/abs/2004.07944" target="_blank">"Cityscapes-Panoptic-Parts and PASCAL-Panoptic-Parts datasets for Scene Understanding"</a>, arXiv 2020.</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2019/01/foggydbfdownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=31'>leftImg8bit_trainval_foggyDBF.zip (20GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=31' target='_blank'>[md5]</a></em> Foggy DBF images (left 8-bit) for train and val sets (3475 images). Citation: C. Sakaridis, D. Dai, S. Hecker, and L. Van Gool, <a href="https://www.vision.ee.ethz.ch/~csakarid/Model_adaptation_SFSU_dense/">"Model Adaptation with Synthetic and Real Data for Semantic Dense Foggy Scene Understanding"</a>, ECCV 2018.</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2017/12/foggyDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=29'>leftImg8bit_trainvaltest_foggy.zip (30GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=29' target='_blank'>[md5]</a></em> Foggy images (left 8-bit) for train, val, and test sets (5000 images). Citation: C. Sakaridis, D. Dai, and L. Van Gool, <a href="http://people.ee.ethz.ch/~csakarid/SFSU_synthetic/" target="_blank">"Semantic Foggy Scene Understanding with Synthetic Data"</a>, IJCV 2018.</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2017/12/foggyDownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=30'>leftImg8bit_trainextra_foggy.zip (40GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=30' target='_blank'>[md5]</a></em> Foggy images (left 8-bit) for trainextra set (19997 images). Citation: C. Sakaridis, D. Dai, and L. Van Gool, <a href="http://people.ee.ethz.ch/~csakarid/SFSU_synthetic/" target="_blank">"Semantic Foggy Scene Understanding with Synthetic Data"</a>, IJCV 2018.</p></li><li id='li1' class='li1' style='background: url(https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2019/07/raindownload.png) no-repeat no-repeat; background-size: 160px 90px; padding-left: 170px; '><p><em><a href='https://www.cityscapes-dataset.com/file-handling/?packageID=33'>leftImg8bit_trainval_rain.zip (21GB)</a> <a href='https://www.cityscapes-dataset.com/md5-sum/?packageID=33' target='_blank'>[md5]</a></em> Rain images (left 8-bit) for parts of train and val sets (295 images, 36 variants each). Citation: X. Hu, C.-W. Fu, L. Zhu, and P.-A. Heng, <a href="http://openaccess.thecvf.com/content_CVPR_2019/html/Hu_Depth-Attentional_Features_for_Single-Image_Rain_Removal_CVPR_2019_paper.html" target="_blank">"Depth-Attentional Features for Single-Image Rain Removal"</a>, CVPR 2019.</p></li></ul></div></div> |
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