Releasing the World's Largest Street-level Imagery Dataset for Teaching Machines to See

Today we present the Mapillary Vistas Dataset--the world's largest and most diverse publicly available, pixel-accurately and instance-specifically annotated street-level imagery dataset for empowering autonomous mobility and transport at the global scale. Since we started our expedition to collaboratively visualize the world with street-level images, we have collected more than 130 million images from places all around the globe. While this number keeps growing at a frantic pace, we are putting serious efforts into researching, implementing, publishing, and releasing smarter computer vision models that can help us understand the semantics within this data. As stated in an earlier blog post, we keep advancing supervised deep learning models as our primary workhorses to extract information that is valuable to our community and improve our products. However, such models are inherently hungry for data--and in particular for a lot of precisely annotated data.