{"id":65835,"date":"2020-11-24T16:17:35","date_gmt":"2020-11-24T15:17:35","guid":{"rendered":"http:\/\/www.prophesee.ai\/?p=65835"},"modified":"2023-01-21T15:30:21","modified_gmt":"2023-01-21T07:30:21","slug":"automotive-megapixel-event-based-dataset","status":"publish","type":"post","link":"https:\/\/www.prophesee-cn.com\/en\/2020\/11\/24\/automotive-megapixel-event-based-dataset\/","title":{"rendered":"Following Machine Learning Spotlight Paper Publication at NeurIPS 2020, Prophesee releases the most comprehensive Event-Based Dataset to date"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; fullwidth=&#8221;on&#8221; _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_fullwidth_code _builder_version=&#8221;4.16&#8243; hover_enabled=&#8221;0&#8243; global_colors_info=&#8221;{}&#8221; sticky_enabled=&#8221;0&#8243;]\n\t\t\t<!-- START NEURIPS 1MP DATASET HEADER REVOLUTION SLIDER 6.7.34 --><p class=\"rs-p-wp-fix\"><\/p>\n\t\t\t<rs-module-wrap id=\"rev_slider_67_1_wrapper\" data-source=\"gallery\" style=\"visibility:hidden;background:rgba(255,255,255,0);padding:0;margin:0px auto;margin-top:-70px;margin-bottom:0px;\">\n\t\t\t\t<rs-module id=\"rev_slider_67_1\" style=\"\" data-version=\"6.7.34\">\n\t\t\t\t\t<rs-slides style=\"overflow: hidden; position: absolute;\">\n\t\t\t\t\t\t<rs-slide style=\"position: absolute;\" data-key=\"rs-105\" data-title=\"Intro\" data-anim=\"ms:3000;\" data-in=\"o:-0.5;sx:1.6;sy:1.6;e:power3.inOut;\" data-out=\"o:0;sx:0.6;sy:0.6;e:power3.inOut;\">\n\t\t\t\t\t\t\t<img decoding=\"async\" src=\"\/\/www.prophesee-cn.com\/wp-content\/plugins\/revslider\/sr6\/assets\/assets\/dummy.png\" alt=\"\" title=\"split-dataset-image-1\" width=\"1920\" height=\"1080\" class=\"rev-slidebg tp-rs-img rs-lazyload\" data-lazyload=\"\/\/www.prophesee-cn.com\/wp-content\/uploads\/2023\/01\/split-dataset-image-1.jpg\" data-parallax=\"10\" data-no-retina>\n<!--\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-67-slide-105-layer-1\" \n\t\t\t\t\t\t\t\tdata-type=\"text\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;y:m;yo:0,-3px,-16px,32px;\"\n\t\t\t\t\t\t\t\tdata-text=\"w:normal;s:50,40,35,26;l:50,50,40,31;fw:700;a:center;\"\n\t\t\t\t\t\t\t\tdata-dim=\"w:689px,546px,529px,373px;\"\n\t\t\t\t\t\t\t\tdata-rsp_bd=\"off\"\n\t\t\t\t\t\t\t\tdata-frame_1=\"sR:10;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;sR:8690;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:5;background-color:rgba(193,207,221,0);font-family:'Montserrat';\"\n\t\t\t\t\t\t\t>PROPHESEE 1 MEGAPIXEL \nAUTOMOTIVE\nDETECTION\nDATASET \n\t\t\t\t\t\t\t<\/rs-layer><!--\n\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-67-slide-105-layer-2\" \n\t\t\t\t\t\t\t\tclass=\"tp-shape tp-shapewrapper\"\n\t\t\t\t\t\t\t\tdata-type=\"shape\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;y:m,t,t,m;yo:110px,351px,245px,108px;\"\n\t\t\t\t\t\t\t\tdata-text=\"a:center;\"\n\t\t\t\t\t\t\t\tdata-dim=\"w:111px;h:7px;\"\n\t\t\t\t\t\t\t\tdata-frame_1=\"sR:10;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;sR:8690;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:6;background-color:#ffffff;\"\n\t\t\t\t\t\t\t> \n\t\t\t\t\t\t\t<\/rs-layer><!--\n-->\t\t\t\t\t<\/rs-slide>\n\t\t\t\t\t<\/rs-slides>\n\t\t\t\t<\/rs-module>\n\t\t\t\t<script>\n\t\t\t\t\tsetREVStartSize({c: 'rev_slider_67_1',rl:[1240,1024,778,480],el:[650,500,350,450],gw:[1200,600,700,480],gh:[650,500,350,450],type:'hero',justify:'',layout:'fullwidth',mh:\"0\"});if (window.RS_MODULES!==undefined && window.RS_MODULES.modules!==undefined && window.RS_MODULES.modules[\"revslider671\"]!==undefined) {window.RS_MODULES.modules[\"revslider671\"].once = false;window.revapi67 = undefined;if (window.RS_MODULES.checkMinimal!==undefined) window.RS_MODULES.checkMinimal()}\n\t\t\t\t<\/script>\n\t\t\t<\/rs-module-wrap>\n\t\t\t<!-- END REVOLUTION SLIDER -->\n[\/et_pb_fullwidth_code][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_row _builder_version=&#8221;4.16&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; custom_padding=&#8221;||0px|||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;|||&#8221; global_colors_info=&#8221;{}&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text _builder_version=&#8221;4.16&#8243; text_font=&#8221;Montserrat||||||||&#8221; text_text_color=&#8221;#1e2534&#8243; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h1 style=\"text-align: center;\"><span>Following the announcement of our Spotlight paper at NeurIPS 2020,\u00a0<\/span><span>Prophesee releases the most comprehensive Event-Based dataset to date.<\/span><\/h1>\n<p><span><\/span><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; fullwidth=&#8221;on&#8221; _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_fullwidth_code _builder_version=&#8221;4.16&#8243; hover_enabled=&#8221;0&#8243; global_colors_info=&#8221;{}&#8221; sticky_enabled=&#8221;0&#8243;]\n\t\t\t<!-- START Dataset 1MPX Automotive Detection banner 1 REVOLUTION SLIDER 6.7.34 --><p class=\"rs-p-wp-fix\"><\/p>\n\t\t\t<rs-module-wrap id=\"rev_slider_68_2_wrapper\" data-source=\"gallery\" style=\"visibility:hidden;background:transparent;padding:0;margin:0px auto;margin-top:0;margin-bottom:0;\">\n\t\t\t\t<rs-module id=\"rev_slider_68_2\" style=\"\" data-version=\"6.7.34\">\n\t\t\t\t\t<rs-slides style=\"overflow: hidden; position: absolute;\">\n\t\t\t\t\t\t<rs-slide style=\"position: absolute;\" data-key=\"rs-106\" data-title=\"Slide\" data-in=\"o:0;\" data-out=\"a:false;\">\n\t\t\t\t\t\t\t<img decoding=\"async\" src=\"\/\/www.prophesee-cn.com\/wp-content\/plugins\/revslider\/sr6\/assets\/assets\/dummy.png\" alt=\"\" title=\"Banner-kpi\" width=\"2000\" height=\"1333\" class=\"rev-slidebg tp-rs-img rs-lazyload\" data-lazyload=\"\/\/www.prophesee-cn.com\/wp-content\/uploads\/2023\/01\/Banner-kpi.jpg\" data-parallax=\"14\" data-panzoom=\"d:5000;e:power3.out;ss:130;se:100;\" data-no-retina>\n<!--\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-68-slide-106-layer-7\" \n\t\t\t\t\t\t\t\tclass=\"tp-shape tp-shapewrapper\"\n\t\t\t\t\t\t\t\tdata-type=\"shape\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;y:m;\"\n\t\t\t\t\t\t\t\tdata-text=\"fw:500;a:inherit;\"\n\t\t\t\t\t\t\t\tdata-dim=\"w:100%;h:100%;\"\n\t\t\t\t\t\t\t\tdata-basealign=\"slide\"\n\t\t\t\t\t\t\t\tdata-rsp_o=\"off\"\n\t\t\t\t\t\t\t\tdata-rsp_bd=\"off\"\n\t\t\t\t\t\t\t\tdata-frame_1=\"e:none;sp:0;sR:10;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;e:power3.out;st:250;sp:3000;sR:240;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:6;background-color:#ffffff;\"\n\t\t\t\t\t\t\t> \n\t\t\t\t\t\t\t<\/rs-layer><!--\n\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-68-slide-106-layer-13\" \n\t\t\t\t\t\t\t\tclass=\"rs-pxl-1\"\n\t\t\t\t\t\t\t\tdata-type=\"text\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;xo:-362px,-329px,-226px,-144px;y:m,m,t,t;yo:-43px,-38px,72px,89px;\"\n\t\t\t\t\t\t\t\tdata-text=\"s:80,70,50,40;l:90,90,80,55;fw:700,700,700,800;a:inherit;\"\n\t\t\t\t\t\t\t\tdata-frame_1=\"sR:10;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;sR:8690;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:9;font-family:'Montserrat';\"\n\t\t\t\t\t\t\t>25M \n\t\t\t\t\t\t\t<\/rs-layer><!--\n\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-68-slide-106-layer-14\" \n\t\t\t\t\t\t\t\tclass=\"rs-pxl-1\"\n\t\t\t\t\t\t\t\tdata-type=\"text\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;xo:-360px,-326px,-231px,-144px;y:m,m,t,t;yo:49px,47px,171px,159px;\"\n\t\t\t\t\t\t\t\tdata-text=\"s:30,30,25,20;l:30,30,30,25;fw:600,600,700,700;a:center;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;sR:8700;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:10;font-family:'Montserrat';\"\n\t\t\t\t\t\t\t>BOXES \n\t\t\t\t\t\t\t<\/rs-layer><!--\n\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-68-slide-106-layer-15\" \n\t\t\t\t\t\t\t\tclass=\"rs-pxl-1\"\n\t\t\t\t\t\t\t\tdata-type=\"text\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:l,c,c,c;xo:593px,11px,0,0;y:m,m,t,t;yo:-43px,-38px,68px,86px;\"\n\t\t\t\t\t\t\t\tdata-text=\"s:80,70,50,40;l:90,90,80,55;fw:700,700,700,800;a:inherit;\"\n\t\t\t\t\t\t\t\tdata-frame_1=\"sR:10;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;sR:8690;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:7;font-family:'Montserrat';\"\n\t\t\t\t\t\t\t>15 \n\t\t\t\t\t\t\t<\/rs-layer><!--\n\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-68-slide-106-layer-16\" \n\t\t\t\t\t\t\t\tclass=\"rs-pxl-1\"\n\t\t\t\t\t\t\t\tdata-type=\"text\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;xo:14px,10px,2px,0;y:m,m,t,t;yo:49px,46px,171px,161px;\"\n\t\t\t\t\t\t\t\tdata-text=\"s:30,30,25,20;l:30,30,30,25;fw:600,600,700,700;a:center;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;sR:8700;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:8;font-family:'Montserrat';\"\n\t\t\t\t\t\t\t>HOURS <\/br>  \n\t\t\t\t\t\t\t<\/rs-layer><!--\n\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-68-slide-106-layer-17\" \n\t\t\t\t\t\t\t\tclass=\"rs-pxl-1\"\n\t\t\t\t\t\t\t\tdata-type=\"text\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:r,c,c,c;xo:123px,304px,240px,138px;y:t,m,m,t;yo:66px,-38px,-38px,88px;\"\n\t\t\t\t\t\t\t\tdata-text=\"s:80,70,50,40;l:90,90,80,55;fw:700,700,700,800;a:inherit;\"\n\t\t\t\t\t\t\t\tdata-frame_1=\"sR:10;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;sR:8690;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:9;font-family:'Montserrat';\"\n\t\t\t\t\t\t\t>1MPx \n\t\t\t\t\t\t\t<\/rs-layer><!--\n\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-68-slide-106-layer-18\" \n\t\t\t\t\t\t\t\tclass=\"rs-pxl-1\"\n\t\t\t\t\t\t\t\tdata-type=\"text\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;xo:392px,316px,238px,138px;y:m,m,t,t;yo:49px,48px,171px,160px;\"\n\t\t\t\t\t\t\t\tdata-text=\"s:30,30,25,20;l:30,30,30,25;fw:600,600,700,700;a:center;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;sR:8700;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:10;font-family:'Montserrat';\"\n\t\t\t\t\t\t\t>HD RESOLUTION \n\t\t\t\t\t\t\t<\/rs-layer><!--\n\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-68-slide-106-layer-23\" \n\t\t\t\t\t\t\t\tclass=\"tp-iefixlayer tp-shape tp-shapewrapper\"\n\t\t\t\t\t\t\t\tdata-type=\"shape\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;y:m;\"\n\t\t\t\t\t\t\t\tdata-text=\"fw:100;a:inherit;\"\n\t\t\t\t\t\t\t\tdata-dim=\"w:100%;h:100%;\"\n\t\t\t\t\t\t\t\tdata-vbility=\"f,f,f,f\"\n\t\t\t\t\t\t\t\tdata-basealign=\"slide\"\n\t\t\t\t\t\t\t\tdata-frame_1=\"sR:10;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;sR:8690;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:5;background-color:rgba(204,204,204,0.75);\"\n\t\t\t\t\t\t\t> \n\t\t\t\t\t\t\t<\/rs-layer><!--\n-->\t\t\t\t\t<\/rs-slide>\n\t\t\t\t\t<\/rs-slides>\n\t\t\t\t<\/rs-module>\n\t\t\t\t<script>\n\t\t\t\t\tsetREVStartSize({c: 'rev_slider_68_2',rl:[1240,1024,778,480],el:[300,300,300,300],gw:[1240,1024,778,480],gh:[300,300,300,300],type:'hero',justify:'',layout:'fullwidth',mh:\"0\"});if (window.RS_MODULES!==undefined && window.RS_MODULES.modules!==undefined && window.RS_MODULES.modules[\"revslider682\"]!==undefined) {window.RS_MODULES.modules[\"revslider682\"].once = false;window.revapi68 = undefined;if (window.RS_MODULES.checkMinimal!==undefined) window.RS_MODULES.checkMinimal()}\n\t\t\t\t<\/script>\n\t\t\t<\/rs-module-wrap>\n\t\t\t<!-- END REVOLUTION SLIDER -->\n[\/et_pb_fullwidth_code][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.16&#8243; min_height=&#8221;245px&#8221; custom_padding=&#8221;0px||0px|||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row _builder_version=&#8221;4.16&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;50px||50px||true|&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.16&#8243; text_font=&#8221;Montserrat||||||||&#8221; text_text_color=&#8221;#1e2534&#8243; custom_margin=&#8221;||14px|||&#8221; custom_padding=&#8221;||0px|||&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h3 style=\"text-align: left;\">ADDRESSING THE PERFORMANCE CHALLENGE<\/h3>\n<p>[\/et_pb_text][et_pb_divider color=&#8221;#000000&#8243; divider_weight=&#8221;5px&#8221; _builder_version=&#8221;4.16&#8243; max_width=&#8221;10%&#8221; module_alignment=&#8221;left&#8221; height=&#8221;0px&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_divider][et_pb_text _builder_version=&#8221;4.16&#8243; _module_preset=&#8221;default&#8221; text_text_color=&#8221;#1e2534&#8243; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span style=\"font-size: medium;\">Event cameras encode visual information with high temporal precision, low data-rate, and high-dynamic range. Thanks to these characteristics, event cameras are particularly suited for scenarios with high motion, challenging lighting conditions and requiring low latency. However, due to the novelty of the field, the performance of event-based systems on many vision tasks is still lower compared to conventional frame-based solutions.\u00a0<\/span><\/p>\n<p><span style=\"font-size: medium;\">The main reasons for this performance gap are: the lower spatial resolution of event sensors, compared to frame cameras; the lack of large-scale training datasets; the absence of well-established deep learning architectures for event-based processing.<\/span><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.16&#8243; background_color=&#8221;#1e2534&#8243; custom_padding=&#8221;0px|0px|50px|0px||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row column_structure=&#8221;1_2,1_2&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;50px|0px|0px|0px||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;1_2&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;|||&#8221; global_colors_info=&#8221;{}&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text _builder_version=&#8221;4.16&#8243; text_font=&#8221;Montserrat||||||||&#8221; text_text_color=&#8221;#ffffff&#8221; header_text_color=&#8221;#ffffff&#8221; custom_margin=&#8221;||14px|||&#8221; custom_padding=&#8221;||0px|||&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h3 style=\"text-align: left;\"><span style=\"color: #ffffff;\">OUR APPROACH<\/span><\/h3>\n<p>[\/et_pb_text][et_pb_divider color=&#8221;#ffffff&#8221; divider_weight=&#8221;5px&#8221; _builder_version=&#8221;4.16&#8243; max_width=&#8221;10%&#8221; module_alignment=&#8221;left&#8221; height=&#8221;0px&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_divider][et_pb_text _builder_version=&#8221;4.16&#8243; text_font=&#8221;||||||||&#8221; text_text_color=&#8221;#ffffff&#8221; inline_fonts=&#8221;Montserrat&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span style=\"font-size: medium;\">Our model, spotlighted at NeurIPS, outperforms by a large margin feed-forward event-based architectures.<\/span><\/p>\n<p><span style=\"font-size: medium;\">Moreover, <strong>our method does not require any reconstruction of intensity images<\/strong> from events, showing that training directly from raw events is possible, <strong>more efficient<\/strong>, and <strong>more accurate<\/strong> than passing through an intermediate intensity image.<\/span><\/p>\n<p><span style=\"font-size: medium;\">Experiments on the algorithmically generated dataset introduced in this work, for which events and gray level images are available, show <strong>performance on par with that of highly tuned and studied frame-based detectors.<\/strong><\/span><\/p>\n<p><span style=\"font-size: medium;\">You can see for yourself and explore the possibilities of this dataset with the machine learning module available in our <strong><a href=\"https:\/\/www.prophesee.ai\/metavision-intelligence\/\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"Metavision Intelligence Suite.\">Metavision Intelligence Suite.<\/a><\/strong><\/span><\/p>\n<p>[\/et_pb_text][\/et_pb_column][et_pb_column type=&#8221;1_2&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;|||&#8221; global_colors_info=&#8221;{}&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_image src=&#8221;https:\/\/www.prophesee-cn.com\/wp-content\/uploads\/2020\/11\/NeurIPS-Prophesee-Machine-Learning-.jpg&#8221; title_text=&#8221;NeurIPS-Prophesee-Machine-Learning-&#8221; show_in_lightbox=&#8221;on&#8221; _builder_version=&#8221;4.19.4&#8243; _module_preset=&#8221;default&#8221; hover_enabled=&#8221;0&#8243; global_colors_info=&#8221;{}&#8221; sticky_enabled=&#8221;0&#8243;][\/et_pb_image][et_pb_text _builder_version=&#8221;4.16&#8243; _module_preset=&#8221;default&#8221; text_text_color=&#8221;#ffffff&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><strong>Fig 1: Conv-rnn feature extractor for object detection unrolled in time<\/strong><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=&#8221;4.16&#8243; _module_preset=&#8221;default&#8221; custom_padding=&#8221;||24px|||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_button button_url=&#8221;https:\/\/papers.nips.cc\/paper\/2020\/file\/c213877427b46fa96cff6c39e837ccee-Paper.pdf&#8221; url_new_window=&#8221;on&#8221; button_text=&#8221;READ THE PAPER&#8221; button_alignment=&#8221;center&#8221; button_alignment_tablet=&#8221;&#8221; button_alignment_phone=&#8221;center&#8221; button_alignment_last_edited=&#8221;on|phone&#8221; _builder_version=&#8221;4.16&#8243; custom_button=&#8221;on&#8221; button_text_color=&#8221;#ffffff&#8221; button_bg_color=&#8221;#407ec9&#8243; button_border_color=&#8221;rgba(0,0,0,0)&#8221; button_border_radius=&#8221;0px&#8221; button_font=&#8221;||||||||&#8221; button_use_icon=&#8221;off&#8221; custom_margin=&#8221;0px||||false|false&#8221; custom_margin_tablet=&#8221;&#8221; custom_margin_phone=&#8221;&#8221; custom_margin_last_edited=&#8221;on|desktop&#8221; custom_padding=&#8221;4px||&#8221; button_text_color_hover=&#8221;#ffffff&#8221; button_border_color_hover=&#8221;#407ec9&#8243; button_bg_color_hover=&#8221;#407ec9&#8243; global_colors_info=&#8221;{}&#8221; button_text_size__hover_enabled=&#8221;off&#8221; button_one_text_size__hover_enabled=&#8221;off&#8221; button_two_text_size__hover_enabled=&#8221;off&#8221; button_text_color__hover_enabled=&#8221;on&#8221; button_text_color__hover=&#8221;#1e2534&#8243; button_one_text_color__hover_enabled=&#8221;off&#8221; button_two_text_color__hover_enabled=&#8221;off&#8221; button_border_width__hover_enabled=&#8221;off&#8221; button_one_border_width__hover_enabled=&#8221;off&#8221; button_two_border_width__hover_enabled=&#8221;off&#8221; button_border_color__hover_enabled=&#8221;on&#8221; button_border_color__hover=&#8221;#1e2534&#8243; button_one_border_color__hover_enabled=&#8221;off&#8221; button_two_border_color__hover_enabled=&#8221;off&#8221; button_border_radius__hover_enabled=&#8221;off&#8221; button_one_border_radius__hover_enabled=&#8221;off&#8221; button_two_border_radius__hover_enabled=&#8221;off&#8221; button_letter_spacing__hover_enabled=&#8221;off&#8221; button_one_letter_spacing__hover_enabled=&#8221;off&#8221; button_two_letter_spacing__hover_enabled=&#8221;off&#8221; button_bg_color__hover_enabled=&#8221;on&#8221; button_bg_color__hover=&#8221;#ffffff&#8221; button_one_bg_color__hover_enabled=&#8221;off&#8221; button_two_bg_color__hover_enabled=&#8221;off&#8221;][\/et_pb_button][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;50px|||||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row column_structure=&#8221;1_2,1_2&#8243; make_equal=&#8221;on&#8221; _builder_version=&#8221;4.16&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; module_alignment=&#8221;center&#8221; custom_padding=&#8221;0px|||||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;1_2&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;30px||||false|false&#8221; global_colors_info=&#8221;{}&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_code _builder_version=&#8221;4.16&#8243; custom_margin=&#8221;||-1px|||&#8221; global_colors_info=&#8221;{}&#8221;]\n\t\t\t<!-- START NEURIPS 1MP DATASET VIDEO REVOLUTION SLIDER 6.7.34 --><p class=\"rs-p-wp-fix\"><\/p>\n\t\t\t<rs-module-wrap id=\"rev_slider_69_3_wrapper\" data-source=\"gallery\" style=\"visibility:hidden;background:transparent;padding:0;margin:0px auto;margin-top:0;margin-bottom:0;\">\n\t\t\t\t<rs-module id=\"rev_slider_69_3\" style=\"\" data-version=\"6.7.34\">\n\t\t\t\t\t<rs-slides style=\"overflow: hidden; position: absolute;\">\n\t\t\t\t\t\t<rs-slide style=\"position: absolute;\" data-key=\"rs-107\" data-title=\"Intro\" data-anim=\"ms:3000;\" data-in=\"o:-0.5;sx:1.6;sy:1.6;e:power3.inOut;\" data-out=\"o:0;sx:0.6;sy:0.6;e:power3.inOut;\">\n\t\t\t\t\t\t\t<img decoding=\"async\" src=\"\/\/www.prophesee-cn.com\/wp-content\/plugins\/revslider\/sr6\/assets\/assets\/dummy.png\" alt=\"\" title=\"split-dataset-image-1\" width=\"1920\" height=\"1080\" class=\"rev-slidebg tp-rs-img rs-lazyload\" data-lazyload=\"\/\/www.prophesee-cn.com\/wp-content\/uploads\/2023\/01\/split-dataset-image-1.jpg\" data-parallax=\"10\" data-no-retina>\n\t\t\t\t\t\t\t<rs-bgvideo \n\t\t\t\t\t\t\t\tdata-video=\"w:100%;h:100%;nse:false;l:loopandnoslidestop;ptimer:false;vfc:true;\"\n\t\t\t\t\t\t\t\tdata-mp4=\"\/\/v.prophesee-cn.com\/sv\/12e5936d-185d34c100e\/12e5936d-185d34c100e.mp4\"\n\t\t\t\t\t\t\t><\/rs-bgvideo>\n<!--\n\t\t\t\t\t\t\t--><rs-layer\n\t\t\t\t\t\t\t\tid=\"slider-69-slide-107-layer-6\" \n\t\t\t\t\t\t\t\tdata-type=\"image\"\n\t\t\t\t\t\t\t\tdata-rsp_ch=\"on\"\n\t\t\t\t\t\t\t\tdata-xy=\"x:c;y:b,t,t,t;yo:24px,497px,382px,306px;\"\n\t\t\t\t\t\t\t\tdata-text=\"l:22;a:inherit;\"\n\t\t\t\t\t\t\t\tdata-dim=\"w:220px,203px,228px,176px;h:20px,18px,20px,16px;\"\n\t\t\t\t\t\t\t\tdata-frame_999=\"o:0;st:w;sR:8700;\"\n\t\t\t\t\t\t\t\tstyle=\"z-index:7;\"\n\t\t\t\t\t\t\t><img decoding=\"async\" src=\"\/\/www.prophesee-cn.com\/wp-content\/plugins\/revslider\/sr6\/assets\/assets\/dummy.png\" alt=\"\" class=\"tp-rs-img rs-lazyload\" width=\"1985\" height=\"178\" data-lazyload=\"\/\/www.prophesee-cn.com\/wp-content\/uploads\/2023\/01\/Fichier-1@3x.png\" data-no-retina> \n\t\t\t\t\t\t\t<\/rs-layer><!--\n-->\t\t\t\t\t<\/rs-slide>\n\t\t\t\t\t<\/rs-slides>\n\t\t\t\t<\/rs-module>\n\t\t\t\t<script>\n\t\t\t\t\tsetREVStartSize({c: 'rev_slider_69_3',rl:[1240,1024,778,480],el:[700,550,450,350],gw:[1200,600,700,600],gh:[700,550,450,350],type:'hero',justify:'',layout:'fullwidth',mh:\"0\"});if (window.RS_MODULES!==undefined && window.RS_MODULES.modules!==undefined && window.RS_MODULES.modules[\"revslider693\"]!==undefined) {window.RS_MODULES.modules[\"revslider693\"].once = false;window.revapi69 = undefined;if (window.RS_MODULES.checkMinimal!==undefined) window.RS_MODULES.checkMinimal()}\n\t\t\t\t<\/script>\n\t\t\t<\/rs-module-wrap>\n\t\t\t<!-- END REVOLUTION SLIDER -->\n[\/et_pb_code][\/et_pb_column][et_pb_column type=&#8221;1_2&#8243; _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.16&#8243; text_font=&#8221;Montserrat||||||||&#8221; text_text_color=&#8221;#1e2534&#8243; custom_padding=&#8221;||0px|||&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h3 style=\"text-align: left;\">DATASET CONTENT<\/h3>\n<p>[\/et_pb_text][et_pb_divider color=&#8221;#000000&#8243; divider_weight=&#8221;5px&#8221; _builder_version=&#8221;4.16&#8243; max_width=&#8221;10%&#8221; module_alignment=&#8221;left&#8221; height=&#8221;0px&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_divider][et_pb_text _builder_version=&#8221;4.16&#8243; text_font=&#8221;Montserrat||||||||&#8221; text_text_color=&#8221;#1e2534&#8243; custom_padding=&#8221;||1px|||&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span style=\"font-size: medium;\">The dataset is split between train, test and val folders.\u00a0<\/span><\/p>\n<p><span style=\"font-size: medium;\">Files consist of 60 seconds recordings that were cut from longer recording sessions. Cuts from a single recording session are all in the same training split.<\/span><\/p>\n<p><span style=\"font-size: medium;\">Each dat file is a binary file in which events are encoded using 4 bytes (unsigned int32) for the timestamps and 4 bytes (unsigned int32) for the data, encoding is little-endian ordering.<\/span><\/p>\n<p><span style=\"font-size: medium;\">The data is composed of 14 bits for the x position, 14 bits for the y position and 1 bit for the polarity (encoded as -1\/1).<\/span><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=&#8221;1_2,1_2&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;||0px|||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;1_2&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;||30px||false|false&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_gallery gallery_ids=&#8221;65844,65845,65846,65877&#8243; fullwidth=&#8221;on&#8221; _builder_version=&#8221;4.16&#8243; width=&#8221;100%&#8221; module_alignment=&#8221;center&#8221; auto=&#8221;on&#8221; auto_speed=&#8221;3000&#8243; global_colors_info=&#8221;{}&#8221;][\/et_pb_gallery][\/et_pb_column][et_pb_column type=&#8221;1_2&#8243; _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.16&#8243; text_text_color=&#8221;#1e2534&#8243; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span style=\"font-size: medium;\">Annotations use the\u00a0<a class=\"external-link\" href=\"https:\/\/numpy.org\/\" rel=\"nofollow noopener noreferrer\" target=\"_blank\">numpy\u00a0<\/a>format and can simply be loaded form python using numpy\u00a0<code>boxes = np.load(path)<\/code><\/span><\/p>\n<p><span style=\"font-size: medium;\">Boxes have the following fields<\/span><\/p>\n<ul>\n<li><span style=\"font-size: medium;\"><strong><em>x<\/em><\/strong> abscissa of the top left corner in pixels<\/span><\/li>\n<li><span style=\"font-size: medium;\"><strong><em>y<\/em><\/strong> ordinate of the top left corner in pixels<\/span><\/li>\n<li><span style=\"font-size: medium;\"><strong><em>w<\/em><\/strong> width of the boxes in pixel<\/span><\/li>\n<li><span style=\"font-size: medium;\"><strong><em>h<\/em><\/strong> height of the boxes in pixel<\/span><\/li>\n<li><span style=\"font-size: medium;\"><strong><em>ts<\/em><\/strong> timestamp of the box in the sequence in microseconds<\/span><\/li>\n<li><span style=\"font-size: medium;\"><strong><em>class_id 0<\/em><\/strong> for pedestrians,<strong><em> 1 <\/em><\/strong>for two wheelers,<em><\/em><strong><em> 2 <\/em><\/strong>for cars,<strong><em> 3 <\/em><\/strong>for trucks,<strong><em> 4<\/em><\/strong> for buses,<strong><em> 5 <\/em><\/strong>for traffic signs,<strong><em> 6 <\/em><\/strong>for traffic lights<\/span><\/li>\n<\/ul>\n<p><span style=\"font-size: medium;\">Alongside the dataset, we also release sample code in Python to conveniently read the events and annotations: <a href=\"https:\/\/github.com\/prophesee-ai\/prophesee-automotive-dataset-toolbox\" target=\"_blank\" rel=\"noopener noreferrer\"><span color=\"#ff7276\" style=\"color: #407ec9;\">Github repository<\/span><\/a><\/span><\/p>\n<p class=\"p1\"><span style=\"font-size: medium;\">For more information on how the dataset was created, <a href=\"https:\/\/papers.nips.cc\/paper\/2020\/file\/c213877427b46fa96cff6c39e837ccee-Paper.pdf\" target=\"_blank\" rel=\"noopener noreferrer\">please refer to the paper.<\/a>\u00a0<\/span><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.16&#8243; background_color=&#8221;#1e2534&#8243; custom_padding=&#8221;50px|0px|50px|0px||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;0px|0px|0px|0px||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;|||&#8221; global_colors_info=&#8221;{}&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text _builder_version=&#8221;4.16&#8243; text_font=&#8221;Montserrat||||||||&#8221; text_text_color=&#8221;#ffffff&#8221; header_text_color=&#8221;#ffffff&#8221; header_3_text_color=&#8221;#ffffff&#8221; custom_padding=&#8221;4px||0px|||&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h3 style=\"text-align: left;\">CITING PROPHESEE 1 MEGAPIXEL AUTOMOTIVE DETECTION DATASET<\/h3>\n<p>[\/et_pb_text][et_pb_divider color=&#8221;#ffffff&#8221; divider_weight=&#8221;5px&#8221; _builder_version=&#8221;4.16&#8243; max_width=&#8221;10%&#8221; module_alignment=&#8221;left&#8221; height=&#8221;0px&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_divider][et_pb_text _builder_version=&#8221;4.16&#8243; text_font=&#8221;||||||||&#8221; text_text_color=&#8221;#ffffff&#8221; inline_fonts=&#8221;Montserrat&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<p><span style=\"font-size: medium;\">When using the data in an academic context, please cite the following paper:<\/span><\/p>\n<p><span style=\"font-size: medium;\">Etienne Perot, Pierre de Tournemire, Davide Nitti, Jonathan Masci, Amos Sironi <a href=\"https:\/\/papers.nips.cc\/paper\/2020\/file\/c213877427b46fa96cff6c39e837ccee-Paper.pdf\" target=\"_blank\" rel=\"noopener noreferrer\" title=\"&quot;Learning to Detect Objects with a 1 Megapixel Event Camera&quot;\">&#8220;Learning to Detect Objects with a 1 Megapixel Event Camera&#8221;<\/a>.<\/span><span style=\"font-size: medium;\">\u00a0<span>To appear in 34th Conference on Neural Information Processing Systems (NeurIPS 2020).<\/span><\/span><\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;50px|||||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.16&#8243; text_font=&#8221;Montserrat||||||||&#8221; text_text_color=&#8221;#1e2534&#8243; custom_padding=&#8221;||0px|||&#8221; global_colors_info=&#8221;{}&#8221;]<\/p>\n<h3 style=\"text-align: left;\">DOWNLOAD PROPHESEE 1 MEGAPIXEL AUTOMOTIVE DETECTION DATASET<\/h3>\n<p>[\/et_pb_text][et_pb_divider color=&#8221;#000000&#8243; divider_weight=&#8221;5px&#8221; _builder_version=&#8221;4.16&#8243; max_width=&#8221;10%&#8221; module_alignment=&#8221;left&#8221; height=&#8221;0px&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_divider][et_pb_code _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;]<iframe frameborder=\"0\" style=\"height:1400px;width:100%;border:none;\" src='https:\/\/forms.zohopublic.com\/itdesk175\/form\/Dataset1MegapixelAutomotiveDetection\/formperma\/m8gOxbwaLFXc2PaLpalHNXeKpq4Tdci1DL0Ynx8q_FE'><\/iframe>[\/et_pb_code][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.16&#8243; background_color=&#8221;#d8dfec&#8221; custom_padding=&#8221;0px||30px|||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_row _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;47px|||||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_text _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;]<\/p>\n<div class=\"et_pb_module et_pb_text et_pb_text_10  et_pb_text_align_left et_pb_bg_layout_light\">\n<div class=\"et_pb_text_inner\">\n<h4 style=\"text-align: center;\"><strong>Don\u2019t miss a bit, <\/strong><\/h4>\n<h4 style=\"text-align: center;\"><strong>follow us to be the first to know<\/strong><\/h4>\n<\/div>\n<\/div>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row make_equal=&#8221;on&#8221; _builder_version=&#8221;4.16&#8243; width=&#8221;100%&#8221; max_width=&#8221;631px&#8221; module_alignment=&#8221;center&#8221; custom_padding=&#8221;0px|||||&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_code _builder_version=&#8221;4.16&#8243; text_orientation=&#8221;center&#8221; module_alignment=&#8221;center&#8221; custom_margin=&#8221;0px||||false|false&#8221; custom_margin_tablet=&#8221;&#8221; custom_margin_phone=&#8221;&#8221; custom_margin_last_edited=&#8221;on|desktop&#8221; custom_padding=&#8221;|||0px|false|false&#8221; custom_padding_tablet=&#8221;&#8221; custom_padding_phone=&#8221;|||0px|false|false&#8221; custom_padding_last_edited=&#8221;on|phone&#8221; module_alignment_tablet=&#8221;&#8221; module_alignment_phone=&#8221;&#8221; module_alignment_last_edited=&#8221;on|desktop&#8221; global_colors_info=&#8221;{}&#8221;]<script type=\"text\/javascript\" src=\"https:\/\/proh.maillist-manage.com\/js\/optin.min.js\" onload=\"setupSF('sfd94487816d6fa1c4312839294faa890fa4f7fb4307b7297e','ZCFORMVIEW',false,'light',false,'0')\"><\/script><script type=\"text\/javascript\">function runOnFormSubmit_sfd94487816d6fa1c4312839294faa890fa4f7fb4307b7297e(th){\/*Before submit, if you want to trigger your event, \"include your code here\"*\/};<\/script><\/p>\n<style>#customForm p{display:inline;}        #customForm.quick_form_8_css * {            -webkit-box-sizing: border-box !important;            -moz-box-sizing: border-box !important;            box-sizing: border-box !important;            word-break: break-word;            overflow-wrap: break-word;        }        \/*** RESPONSIVE START *\/        @media only screen and (max-width: 200px) {            .quick_form_8_css[name='SIGNUP_BODY'] {                width: 100% !important;                min-width: 100% !important;                margin: 0px auto !important;                padding: 0px !important            }        }        \/*Major Mobiles*\/        @media screen and (min-width: 320px) and (max-width: 580px) and (orientation : portrait) {            .quick_form_8_css[name='SIGNUP_BODY'] {                max-width: 300px !important;                margin: 0px auto !important;                padding: 0px !important;            }        }        \/* iPads*\/        @media only screen and (min-device-width : 768px) and (max-device-width:1024px) {            .quick_form_8_css[name='SIGNUP_BODY'] {                max-width: 500px !important;                margin: 0px auto !important;            }        }        @media only screen and (min-device-width : 768px) and (max-device-width : 1024px) and (orientation : landscape) {            .quick_form_8_css[name='SIGNUP_BODY'] {                max-width: 700px !important;                margin: 0px auto !important;            }        }        @media screen and (min-width: 475px) and (max-width: 980px) and (orientation : landscape) {            .quick_form_8_css[name='SIGNUP_BODY'] {                max-width: 400px !important;                margin: 0px auto !important;                padding: 0px !important;            }        }        \/*** RESPONSIVE END *\/    <\/style>\n<div id=\"sfd94487816d6fa1c4312839294faa890fa4f7fb4307b7297e\" data-type=\"signupform\" style=\"opacity: 1;\">\n<div id=\"customForm\">\n<div class=\"quick_form_8_css\" style=\"background-color: rgb(64, 126, 201); width: 350px; z-index: 2; font-family: Arial; border-width: 1px; border-style: solid; border-color: rgb(235, 235, 235); overflow: hidden;\" name=\"SIGNUP_BODY\" bgcolor=\"#407ec9\">\n<div><span style=\"font-size: 14px; font-family: Arial; font-weight: bold; color: rgb(255, 255, 255); text-align: left; padding: 10px 20px 5px; width: 100%; display: block;\" id=\"SIGNUP_HEADING\" bgcolor=\"#ffffff\">\u2709\ufe0f Join Our Newsletter<\/span><\/p>\n<div style=\"position:relative;\">\n<div id=\"Zc_SignupSuccess\" style=\"display:none;position:absolute;margin-left:4%;width:90%;background-color: white; padding: 3px; border: 3px solid rgb(194, 225, 154);  margin-top: 10px;margin-bottom:10px;word-break:break-all\">\n<table width=\"100%\" cellpadding=\"0\" cellspacing=\"0\" border=\"0\">\n<tbody>\n<tr>\n<td width=\"10%\"><img decoding=\"async\" class=\"successicon\" src=\"https:\/\/proh.maillist-manage.com\/images\/challangeiconenable.jpg\" align=\"absmiddle\"><\/td>\n<td><span id=\"signupSuccessMsg\" style=\"color: rgb(73, 140, 132); font-family: sans-serif; font-size: 14px;word-break:break-word\">\u00a0\u00a0Thank you for Signing Up<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<form method=\"POST\" id=\"zcampaignOptinForm\" style=\"margin:0px;width:100%\" action=\"https:\/\/maillist-manage.com\/weboptin.zc\" target=\"_zcSignup\">\n<div style=\"background-color: rgb(255, 235, 232); padding: 10px; color: rgb(210, 0, 0); font-size: 11px; margin: 20px 10px 0px; border: 1px solid rgb(255, 217, 211); opacity: 1;display:none;\" id=\"errorMsgDiv\">Please correct the marked field(s) below.<\/div>\n<div style=\"position:relative;margin: 10px 10px 10px;width: 200px;height: 30px;display: inline-block;\">\n<div id=\"Zc_SignupSuccess\" style=\"position: absolute;width: 87%;background-color: white;padding: 3px;border: 3px solid rgb(194, 225, 154);margin-bottom: 10px;word-break: break-all;opacity: 1;display:none;\">\n<div style=\"width: 20px;padding: 5px;display:table-cell\"><img decoding=\"async\" class=\"successicon\" src=\"https:\/\/campaigns.zoho.com\/images\/challangeiconenable.jpg\" style=\"width:20px;\"><\/div>\n<div style=\"display:table-cell\"><span id=\"signupSuccessMsg\" style=\"color: rgb(73, 140, 132);font-family: sans-serif;font-size: 14px;word-break:break-word;line-height: 30px;display: block;\"><\/span><\/div>\n<\/div>\n<p><input type=\"text\" style=\"font-size: 14px; border: 1px solid rgb(255, 255, 255); border-radius: 0px; width: 100%; height: 100%; z-index: 4; outline: none; padding: 5px 10px; color: rgb(136, 136, 136); text-align: left; font-family: Arial; background-color: rgb(255, 255, 255); box-sizing: border-box;\" placeholder=\"Email\" changeitem=\"SIGNUP_FORM_FIELD\" name=\"CONTACT_EMAIL\" id=\"EMBED_FORM_EMAIL_LABEL\" bgcolor=\"#ffffff\"><\/div>\n<div style=\"position:relative;margin: 10px;width: 100px;height: 30px;text-align: left;display: inline-block;\"><input type=\"button\" style=\"text-align: center; border-radius: 5px; width: 100%; height: 100%; z-index: 5; border: 0px; color: rgb(255, 255, 255); cursor: pointer; outline: none; font-size: 14px; background-color: rgb(30, 37, 52); margin: 0px 0px 0px -5px;\" name=\"SIGNUP_SUBMIT_BUTTON\" id=\"zcWebOptin\" value=\"Join Now\" bgcolor=\"#1e2534\"><\/div>\n<p><input type=\"hidden\" id=\"fieldBorder\" value=\"\"><input type=\"hidden\" id=\"submitType\" name=\"submitType\" value=\"optinCustomView\"><input type=\"hidden\" id=\"emailReportId\" name=\"emailReportId\" value=\"\"><input type=\"hidden\" id=\"formType\" name=\"formType\" value=\"QuickForm\"><input type=\"hidden\" name=\"zx\" id=\"cmpZuid\" value=\"1275f5708\"><input type=\"hidden\" name=\"zcvers\" value=\"3.0\"><input type=\"hidden\" name=\"oldListIds\" id=\"allCheckedListIds\" value=\"\"><input type=\"hidden\" id=\"mode\" name=\"mode\" value=\"OptinCreateView\"><input type=\"hidden\" id=\"zcld\" name=\"zcld\" value=\"13b5dc528caf50ba\"><input type=\"hidden\" id=\"document_domain\" value=\"\"><input type=\"hidden\" id=\"zc_Url\" value=\"proh.maillist-manage.com\"><input type=\"hidden\" id=\"new_optin_response_in\" value=\"0\"><input type=\"hidden\" id=\"duplicate_optin_response_in\" value=\"0\"><input type=\"hidden\" name=\"zc_trackCode\" id=\"zc_trackCode\" value=\"ZCFORMVIEW\" onload=\"\"><input type=\"hidden\" id=\"zc_formIx\" name=\"zc_formIx\" value=\"d94487816d6fa1c4312839294faa890fa4f7fb4307b7297e\"><input type=\"hidden\" id=\"viewFrom\" value=\"URL_ACTION\"><span style=\"display:none\" id=\"dt_CONTACT_EMAIL\">1,true,6,Contact Email,2<\/span><\/form>\n<\/div>\n<\/div>\n<\/div>\n<p><img decoding=\"async\" src=\"https:\/\/proh.maillist-manage.com\/images\/spacer.gif\" id=\"refImage\" onload=\"referenceSetter(this)\" style=\"display:none;\"><\/div>\n<p><input type=\"hidden\" id=\"signupFormType\" value=\"QuickForm_Horizontal\"><\/p>\n<div id=\"zcOptinOverLay\" oncontextmenu=\"return false\" style=\"display:none;text-align: center; background-color: rgb(0, 0, 0); opacity: 0.5; z-index: 100; position: fixed; width: 100%; top: 0px; left: 0px; height: 988px;\"><\/div>\n<div id=\"zcOptinSuccessPopup\" style=\"display:none;z-index: 9999;width: 800px; height: 40%;top: 84px;position: fixed; left: 26%;background-color: #FFFFFF;border-color: #E6E6E6; border-style: solid; border-width: 1px;  box-shadow: 0 1px 10px #424242;padding: 35px;\"><span style=\"position: absolute;top: -16px;right:-14px;z-index:99999;cursor: pointer;\" id=\"closeSuccess\"><img decoding=\"async\" src=\"https:\/\/proh.maillist-manage.com\/images\/videoclose.png\"><\/span><\/p>\n<div id=\"zcOptinSuccessPanel\"><\/div>\n<\/div>\n<p>[\/et_pb_code][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Following the publication of breakthrough paper on machine learning, Prophesee releases the most comprehensive Event-Based Dataset to date with 1Mpx quality and 25M boxes<\/p>\n","protected":false},"author":1,"featured_media":76658,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","inline_featured_image":false,"footnotes":""},"categories":[26,18,24,6],"tags":[21,27,3],"class_list":["post-65835","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-dataset","category-engineers","category-news","category-non-classe","tag-computer-vision","tag-dataset","tag-event-based-vision"],"_links":{"self":[{"href":"https:\/\/www.prophesee-cn.com\/en\/wp-json\/wp\/v2\/posts\/65835","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.prophesee-cn.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.prophesee-cn.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.prophesee-cn.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.prophesee-cn.com\/en\/wp-json\/wp\/v2\/comments?post=65835"}],"version-history":[{"count":0,"href":"https:\/\/www.prophesee-cn.com\/en\/wp-json\/wp\/v2\/posts\/65835\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.prophesee-cn.com\/en\/wp-json\/wp\/v2\/media\/76658"}],"wp:attachment":[{"href":"https:\/\/www.prophesee-cn.com\/en\/wp-json\/wp\/v2\/media?parent=65835"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.prophesee-cn.com\/en\/wp-json\/wp\/v2\/categories?post=65835"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.prophesee-cn.com\/en\/wp-json\/wp\/v2\/tags?post=65835"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}