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/, 0 23/ 0 1 , Mapillary images are available under the Creative Commons Attribution-ShareAlike 4.0 (CC BY-SA 4.0)

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,, /3 12 / 0 1 5 2 9 8 9 4 9 201 The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes doi: 10.1109/ICCV.2017.534

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/, 04 23/ 0 1 , - - - - ( - ( - - ) https://research.mapillary.com/lsun.html

/, 0 23/ 0 1 , 0 2 1 , •Road markings: increased from 6 classes to 21 classes including speed limits and direction arrows, which are essential classes for building navigation and HD maps. •Driveway: a new class that we’ve introduced to help enhance data extraction for last-mile •Barriers: increased from 6 to 11 classes. Detailed refinement of the barrier classes is the first step to enhance the perception capacity for autonomous driving under different scenarios. •Signages: the billboard class is now refined to advertisement, storefront, and general information signages. This facilitates automatic and in-depth location-aware data extraction for marketing, business, and point-of-interest analysis. •Traffic light states: dynamic properties are associated with static objects. In this case, we have refined 100K traffic light annotations with different state

/, 0 23/ 0 1 , http://www.robustvision.net/

/, 0 23/ 0 1 , https://blog.mapillary.com/update/2018/06/14/robust-cv.html

/, 0 23/ 0 1 , http://www.wilddash.cc/benchmark/resultsvis_rob18_sem?hc=semantic_rob

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,, /3 12 / 0 Mapillary Vistas Dataset 25,000 & 152 https://research.mapillary.com/

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/, 04 23/ 0 1 , Thank you! tosseto@csis.u-tokyo.ac.jp http://researchmap.jp/tosseto https://speakerdeck.com/tosseto