[et_pb_section bb_built=”1″ fullwidth=”on” specialty=”off” _builder_version=”3.0.86″ background_image=”https:\/\/ryma.cinvestav.mx\/ravg\/wp-content\/uploads\/sites\/19\/2017\/09\/IMAGEN-CAMPA\u00d1A1.jpg” global_module=”735″][et_pb_fullwidth_header admin_label=”RESOURCES_Title” global_parent=”735″ _builder_version=”3.0.86″ title=”RAVG: Robotics Active Vision” subhead=”Resources” text_orientation=”left” header_fullscreen=”off” header_scroll_down=”off” image_orientation=”center” background_overlay_color=”rgba(0,0,0,0.3)” background_layout=”dark” content_orientation=”center” text_shadow_style=”preset3″ text_shadow_blur_strength=”1em” text_shadow_color=”rgba(0,0,0,0.8)” title_font=”|700|||||||” subhead_font=”|700|||||||” subhead_font_size=”20″ custom_button_two=”off” button_two_icon_placement=”right” custom_button_one=”off” button_one_icon_placement=”right” \/][et_pb_fullwidth_menu global_parent=”735″ _builder_version=”3.0.86″ menu_id=”6″ submenu_direction=”downwards” fullwidth_menu=”off” background_layout=”light” active_link_color=”#8300e9″ menu_font=”|700|||||||” background_color=”#d3d3d3″ \/][\/et_pb_section][et_pb_section bb_built=”1″ admin_label=”Section with nice shadow” _builder_version=”3.0.86″ custom_css_main_element=”box-shadow: inset 0px 3px 2px rgba(50, 50, 50, 0.75);”][et_pb_row _builder_version=”3.0.47″ background_size=”initial” background_position=”top_left” background_repeat=”repeat”][et_pb_column type=”4_4″][et_pb_text _builder_version=”3.0.86″ background_layout=”light”]<\/p>\n
Discriminatively Trained Templates for 3D Object Detection: A Real Time Scalable Approach<\/span>, Notes<\/strong>: Ignore first line of annotation files. Second number is the amount of annotations. Remaining lines of each file have: [#frame \u00a0x \u00a0y \u00a0width \u00a0height]. Evaluation is done considering as correct >=70% overlap, Intersection\/Union. If you use our dataset or any image from it, please cite bibtex<\/a>.<\/p>\n Training<\/strong>:<\/p>\n box<\/a>, camera<\/a>, cokeCan<\/a>, cup<\/a>, gameBoy<\/a>, holePuncher<\/a>, pincers<\/a>, stapler<\/a>, toyCar<\/a>, toyGun<\/a>,<\/p>\n Testing<\/strong>:<\/p>\n box<\/a>, camera<\/a>, cokeCan<\/a>, cup<\/a>, gameBoy<\/a>, holePuncher<\/a>, pincers<\/a>, stapler<\/a>, toyCar<\/a>, toyGun<\/a><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section bb_built=”1″ fullwidth=”off” specialty=”off” background_color=”rgba(0,0,0,0.32)” inner_shadow=”on” custom_css_main_element=”box-shadow: inset 0px 3px 2px rgba(150, 150, 150, 0.85);” _builder_version=”3.0.72″ locked=”off” global_module=”321″][et_pb_row global_parent=”321″ make_fullwidth=”off” use_custom_width=”off” width_unit=”on” use_custom_gutter=”off” allow_player_pause=”off” parallax=”off” parallax_method=”on” make_equal=”off” parallax_1=”off” parallax_method_1=”off” custom_margin=”-40px|||” background_position=”top_left” background_repeat=”repeat” background_size=”initial” parent_locked=”off”][et_pb_column type=”4_4″][et_pb_image admin_label=”LogoCINVESTAV del Pie de p\u00e1gina” global_parent=”321″ src=”https:\/\/ryma.cinvestav.mx\/wp-content\/uploads\/2014\/08\/roboticaCinvestavOK_transparencia_white.png” alt=”Rob\u00f3tica y Manufactura Avanzada, Cinvestav” show_in_lightbox=”off” url_new_window=”off” use_overlay=”off” animation=”off” sticky=”on” align=”center” max_width=”95px” max_width_last_edited=”on|desktop” force_fullwidth=”off” always_center_on_mobile=”on” custom_margin=”||15px|” _builder_version=”3.0.85″ parent_locked=”off” url=”https:\/\/ryma.cinvestav.mx\/” show_bottom_space=”on” \/][et_pb_text global_parent=”321″ _builder_version=”3.0.72″ background_layout=”dark” text_orientation=”center” border_style=”solid” custom_margin=”||-50px|” parent_locked=”off”]<\/p>\n Av. Industrial\u00a0Metalurgia\u00a0#1062,\u00a0Parque Ind. Ramos Arizpe,\u00a0Ramos Arizpe, Coah.\u00a0C.P. 25900, M\u00e9xico. \u00a0Tel. +52 (844) 438-9600<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" Webpage under construction… DataSet ICCV 2013 Discriminatively Trained Templates for 3D Object Detection: A Real Time Scalable Approach, Rios-Cabrera, Reyes, Tuytelaars, Tinne. In International Conference on Computer Vision , ICCV, 2013.\u00a0[PDF] Notes: Ignore first line of annotation files. Second number is the amount of annotations. Remaining lines of each file have: [#frame \u00a0x \u00a0y \u00a0width […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":9,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"class_list":["post-547","page","type-page","status-publish","hentry"],"yoast_head":"\n
\nRios-Cabrera, Reyes,<\/strong> Tuytelaars, Tinne.
\nIn International Conference on Computer Vision , ICCV<\/strong>,<\/em> 2013.\u00a0[PDF<\/a>]<\/p>\n
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