Introducing Smart Edits: AI-assisted map-editing for point features with JOSM and Mapillary
Today, we’re introducing a new capability in the Mapillary plugin for JOSM, which allows for adding AI-detected map features using an accelerated workflow. Objects that were detected from Mapillary street level imagery can now be added to the map with just a few clicks.
Turn a Tesla into a mapping vehicle with Mapillary
Tesla vehicles have often been described as “computers on wheels”. They also include cameras for assisted driving features. In the Mapillary community, these features have raised the question whether the imagery from the car’s cameras could be collected and uploaded to Mapillary. In this post, we present a solution to do exactly that.
Microsoft Open Maps: Using Mapillary to improve OpenStreetMap in Serbia
Over the last couple of years the Microsoft Open Data Team in Serbia has been very busy. They've contributed over 1,000,000 images on 8,000 km of roads. They've also validated 300,000 traffic signs and made more than 4,000 traffic sign related edits in OSM.
The Latest and Greatest for Mapillary in OSM iD for November 2020
Finding and navigating Mapillary images in iD Editor has been significantly improved. Chris walks through these latest improvements.
The evolving camera landscape and our 2020 recommendations.
The hardware landscape for street-level image capable cameras has improved substanially since Mapillary began. We'd like to share our latest thoughts on different camera types and the models we recommend.
Power Mapping brings Rapid Reliable Energy to Rural Communities
Students in chapters across the YouthMappers network are finding innovative ways to use geospatial data and tools to improve Sierra Leone’s electrical grid.
Extending Object Detections to Scene Classes
Today, we are announcing the extension of machine-generated detections to scene classes. The new scene classes cover transportation infrastructure such as gas stations, toll stations, and parking lots and will help cities and community groups speed up their mapping efforts.
Updating our Street Level Image Privacy Blurring
We recently made changes to how we handle image blurring for street level images. This post provides an update and explains those changes for our Mapillary users and contributors.
Global access to map data with the Mapillary API
Anyone can now access Mapillary's map features directly via our API. Read on to see the ways you can filter and download map features programmatically.
Mapillary map features now available globally in OpenStreetMap
Map features are now available in both iD Editor and JOSM. Let us know how they fit into your mapping workflows.
Introducing the Mapillary Planet-Scale Depth Dataset for Single-View Depth Estimation
The Mapillary Planet-Scale Depth dataset is unique in its scale and diversity, thanks to the millions of images that our community uploads to Mapillary every day.
Mapillary Joins Facebook on the Journey of Improving Maps Everywhere
Today we're announcing that Mapillary has joined Facebook on the quest to improve maps everywhere and for everyone.
Towards safer transportation: #map2020 in 2020
After almost 3 months of mapping, groups from around the world have submitted their Map2020 reports. One project has been selected to present at the 2020 Humanitarian OpenStreetMap Summit which will be held later this year.
Learning with Verification: Improving Object Recognition with the Community’s Input
Thanks to our community that verified over half a million machine-generated object detections, we’ve developed an efficient approach to object recognition that helps improve map data quality. We used the verifications to include partially annotated images in our training data, leading to much higher detection accuracy compared to using only fully annotated images. This is a scalable way to get diverse training data for developing models that perform well on real-world object recognition tasks globally.
Achieving More with Street-Level Imagery: Geocortex Adds Support for Mapillary in Geocortex Essentials
Geocortex adds out-of-the-box support for Mapillary imagery and data in their latest Geocortex Essentials release, making it easier than ever for Geocortex's 1500 partners to use street-level imagery for building better GIS solutions.
Introducing the Mapillary Street-Level Sequences Dataset for Lifelong Place Recognition
Today we’re releasing the Mapillary Street-Level Sequences Dataset, the world’s most diverse publicly available dataset for lifelong place recognition. Mapillary Street-Level Sequences is one of our three papers that will be published at CVPR later this year.
Improving Maps for Better Capacity Planning in the Fight Against Covid-19
Better capacity planning needs better maps. By adding hospital bed count to OpenStreetMap, we can all make a difference.
Upgrading Mapillary for JOSM: Focused Editing with Filters
Boost your OpenStreetMap editing with new features in Mapillary's plugin for JOSM: more flexible filters, enhanced changeset tagging, support for organizations, and a number of UI and performance fixes.
Mapping in the Times of Covid-19 and How You Can Help
As the world takes action against the Covid-19 outbreak, here is how you can help.
Launching #map2020 for Improved Navigation in Undermapped Regions
Mapillary and Humanitarian OpenStreetMap Team are launching a new mapping campaign, #map2020, to solve one of the greatest developmental challenges for low- and middle-income countries: maps and navigation. Here’s how you can take part.
Visualize the Future of Cities with Mapillary in ArcGIS Urban
ArcGIS Urban, Esri’s new product for smart city planning, is now featuring a Mapillary integration. Bring street-level imagery side by side with 3D models of projects for a better understanding of how cities will evolve.
Unveiling the Mapping in Logistics Report: The Impact of Broken Maps on Last-Mile Deliveries
We spoke to hundreds of delivery drivers across the US to find out how maps impact their work on a daily basis. It turns out that broken maps are a $6-billion-problem to logistics companies in the US alone.
A Look Back at 2019 and the Road to One Billion Images
The Mapillary platform now hosts one billion high-resolution images from around the world, all open and available for improving maps. With 2019 drawing to a close, we are looking back on some of the events that helped us reach this important milestone.
Unveiling our Latest Research: Multi-Object Tracking and Segmentation from Automatic Annotations
Access to high-quality training data is one of the most important requirements to push the boundaries with machine learning in computer vision. Today we’re unveiling our latest piece of research, where we roll out an entirely new way to generate training data for multi-object tracking and segmentation. The approach turns raw street-level videos into training data with unprecedented quality—even compared to results based on human-annotated data. By allowing machines to generate training data, the cost for training computer vision models can go down substantially. We validate our approach for multi-object tracking and segmentation and obtain new state-of-the-art results. Here is how.
Mapillary on the AWS Marketplace: An Even Easier Way for AWS Customers to Get the Map Data They Need
We have published 20 Mapillary datasets on the AWS Marketplace to make it easier than ever for AWS customers to access the map data they need.
The Data That Paves the Way: How We’re Building the First Open Dataset for HD Maps
We are building the first open dataset for maintaining and updating HD maps with Zenuity, AstaZero, RISE, and AI Innovation of Sweden. Together, we will collect map data in a highly controlled environment through cheap dashcams, lidar, and radar, in an effort to build a cost-effective way of updating HD maps and teaching autonomous vehicles to understand their surroundings through an HD map — even when the surroundings have changed remarkably.
Helping Cities Across the US to Understand Their Streets: Unveiling our Partnership with IWorQ
We’re celebrating GIS Day by unveiling a new partnership with IWorQ, the cloud-based software provider that helps 1300 US municipalities to manage their assets, facilities, licenses, and more. Together, we will help local governments all over the US to capture street-level imagery and understand their streets and roads through computer vision. With the help of computer vision technology, municipalities will get access to more and better data, which will improve decision-making and cut costs.
Accessing Machine-Extracted Map Data: Improved Data Downloads
Downloading the map data that you’ve subscribed to is now much more flexible. You can choose the object types you wish to download, which also means your download files will get prepared faster. There are two new file types available, and notifications for when your data is ready.
Mapillary at ICCV 2019: Unveiling our Latest Benchmark Wins
Mapillary is heading to ICCV for a week packed with activities. Here’s where you will find us.
The Camera That Turns Any Fleet into a Mapping Fleet: Say Hello to the Mapillary Dashcam
Mapillary is releasing the world’s first end-to-end encrypted mapping dashcam to help delivery and ride-sharing fleets access the map and navigation data they need to serve their customers. The camera is light, flexible, and while it requires no extra work from drivers, it can capture up to 150,000 high-quality images in one eight-hour session. The images and the data are available on the Mapillary platform within hours of uploading. Finally, a quick and easy way for fleets to get the map data they need to fix maps.
See Your Mapillary Milestones in the iOS App
Our newest feature in the iOS app lets you see the milestones you’ve reached as a Mapillary contributor, and the next goals that await.
Towards a driverless future: How Mapillary is teaming up with Siemens to teach streetcars to see in a fully autonomous depot
Mapillary is teaming up with Siemens, Germany’s Federal Ministry of Transport and Digital Infrastructure, and others to make driverless streetcars in a self-operating depot a reality. The project takes place in Potsdam and will over the course of three years teach a driverless streetcar to get from A to B with the help of sensor fusion and street-level imagery that Mapillary is turning into map data to allow the streetcar to see.
More Ways to Teach the Machine to See: Spotting Missed Objects
With Verification Projects, you can do quality review of the automatic object detections that underlie Mapillary’s machine-generated map data. In addition to verifying whether detections are correct, you can now also check images for missed objects, as we release a new type of task that’s now available in all verification projects. This will help improve our algorithms even more, enabling you to scale up mapping with high-quality map data.
Welcoming lvl5 Imagery and Contributors to Mapillary
Today we’re announcing hundreds of millions of new images being added to Mapillary. Following lvl5 moving on to new adventures, all images they collected through paid drivers are now coming to Mapillary—and made available to everyone.
Announcing the Winners of #map2020
There were 33 projects submitted for the #map2020 challenge to build better maps in undermapped regions. Mapping teams joined in from Europe, Asia, and Africa for the chance to demonstrate how street-level imagery can play a role in addressing a humanitarian challenge. Two projects were selected to present at the HOT Summit in Germany.
Introducing the Mapillary Partner Program
Many businesses and organizations, ranging from governmental to geospatial and mapping, already take advantage of our global street-level imagery platform to provide solutions for their customers. Today, we are making it easier than ever by announcing the latest and greatest iteration of our partnership program.
Winning at CVPR 2019: Mapillary Tops Two Computer Vision Benchmarking Challenges
At CVPR this year, Mapillary won two computer vision benchmarking challenges. We will always keep pushing the boundaries of what is possible in computer vision, and it is our award-winning models that allow us to produce the highest quality map data possible.
Introducing the Mapillary Traffic Sign Dataset for Teaching Machines to Understand Traffic Signs Globally
Today we’re releasing the Mapillary Traffic Sign Dataset, the world’s most diverse publicly available dataset of traffic sign annotations on street-level imagery that will help improve traffic safety and navigation everywhere. Covering different regions, weather and light conditions, camera sensors, and viewpoints, it enables developing high-performing traffic sign recognition models in both academic and commercial research.
From Ghana to Iraq: How #Map2020 Mappers Use Street-Level Imagery to Tackle Humanitarian Challenges
From Ghana to Iraq, Zambia to the Philippines, we take a look at some of the 33 mapping projects that are taking part in #map2020 to build better maps in undermapped regions. The mapping participants are collecting street-level imagery to improve things like waste management, natural disaster response, and damaged roads, addressing some of the most pressing issues in undermapped regions.
Training Machines to Attain a 3D Understanding of Objects from Single, 2D Images
We sit down with Peter Kontschieder, the Director of Research at Mapillary, to talk about “Disentangling Monocular 3D Object Detection”, the latest academic paper to be published by Mapillary’s Research team. Peter tells us about how 3D object detections made in single 2D images have the ability to improve mapmaking and push down the cost of autonomous vehicles, and how the team unveiled a fundamental flaw in the metric used by the most dominant benchmarking dataset in this area.
Effortless Mapping with a Customized Mapillary Dashcam
Dashcams are the perfect type of camera for hours of imagery capture without needing much interaction from the driver. That’s why we developed the Mapillary edition of BlackVue DR900s, a high-resolution and high-performance dashcam, explicitly optimized for effortless mapping. This custom dashcam makes image collection more efficient while simplifying uploads, enabling both individual mappers and entire fleets to scale up fresh imagery collection for better maps everywhere.
Map Data on Demand: Announcing the Mapillary Marketplace
Today, we launch the world’s first demand-driven marketplace for generating street-level imagery and map data. Mapmakers, cities, and NGOs can post mapping requests that anyone can pick up and help complete. Mapillary’s collaborative contributor network already spans 190 countries and is open for everyone to join and work on map data projects to improve maps, cities, and mobility everywhere.
Scale Imagery Collection with Capture Projects: Android App Now Available
With our recently released Capture Projects, organizations like the City of Detroit have collected thousands of kilometers of fresh street-level imagery by having a team of drivers cover the area, task by task. Today we’re making Mapillary Driver, the app that drivers use for completing their tasks, available on Android. This improves access to Capture Projects as teams are now able to use a broader range of devices in the field to see what they need to map.
Announcing #CompleteTheMap V
#CompleteTheMap is back for the Northern Hemisphere summer. We’re encouraging location submissions from around the world with the goal to capture dense street-level imagery within the challenge area. The top three participants will be awarded cameras for the contributions at the end of the challenge.
Launching #Map2020: A New Campaign for Building Better Maps in Undermapped Regions
Mapillary and Humanitarian OpenStreetMap Team are joining forces to accelerate map data collection in undermapped regions. Local mappers are invited to use street-level imagery in mapping projects that address humanitarian or developmental challenges. Two of the projects submitted to the #map2020 campaign will be selected for a fully-funded trip to HOT Summit in Heidelberg, Germany this September.
Five US Departments of Transportation Upload 270,000 Miles of Road Data to Mapillary to Understand Road Safety
Road safety is a big problem in the US and a key focus for states across the country. In a big step towards ensuring road safety for their residents, Departments of Transportation in Utah, Florida, Arizona, Connecticut, and Vermont have now all made their state photologs publically available on the Mapillary platform. These images cover 270,000 miles of roads and are automatically processed with computer vision to detect guardrails, traffic signs, and pedestrians’ interactions with vehicles at scale.
Improved Viewing Experience: Announcing Combined Panning in the Mapillary Viewer
We've just enhanced the Mapillary viewer with the Combined Panning feature that lets you pan between overlapping regular images just like you would do with a full panorama, simply by dragging with your mouse. This provides a more natural and convenient viewing experience as you navigate among Mapillary imagery to look around in an area.
500 million images available to everyone
We just hit another milestone for our platform. More than 500 million images have been uploaded to Mapillary by our amazing community, customers, and partners worldwide.
Announcing Verification Projects: A Scalable Way of Validating Machine-Generated Data
With Verification Projects, map makers and GIS experts can review machine-extracted map data by adding human validation to the workflow. Comprising a project dashboard and a simple game-based tool for verifying object detections, Verification Projects enable quality assurance of the data available in any area, as well as help to improve Mapillary’s machine learning algorithms with human feedback.
And here are the winners!: Guess When We Hit 500 Million Images and Win a BlackVue Camera
Approaching the 500 millionth images on the Mapillary platform, we invited our community to guess when the 500 millionth image would be uploaded and enter the race to win a BlackVue camera and Mapillary swag.
Introducing Seamless Scene Segmentation: Allowing Machines to Understand Street Scenes Better by Turning Two Models into One
Today we’re announcing that Mapillary will publish four papers at CVPR this year. In this post, we’re looking at the paper named Seamless Scene Segmentation, which, as a world-first, rolls out a new computer vision model that slashes up to 20% computing powers when teaching machines to distinguish between people, cars, and map data like traffic signs, together with its overall environment.
Improved Upload Management in the Desktop Uploader
Uploading thousands of images got even easier with the latest release of the Mapillary Desktop Uploader, which adds functionality for previewing images and managing your upload history. Spend less time handling your uploads and more time improving maps!
Announcing Capture Projects: An Entirely New Way of Collecting Map Data at Scale
Today we’re announcing Capture Projects to help cities, mapmakers, and transportation agencies everywhere ramp up imagery and map data collection. With the release of a new project dashboard and an accompanying app, called Mapillary Driver, organizations can now manage an unlimited number of drivers to capture street-level imagery at any given point, rapidly escalating how quickly maps can be updated at scale.
Doing way more with Less: Catching up with the Mapillary Research Team
Since 2016 when we opened our AI lab in Graz, the research team has been busy publishing papers, winning benchmarking competitions, and developing the building blocks that power Mapillary. Now we are celebrating the opening of a brand new Graz lab and looking back at how it all came together.
Updating Maps with Cameras: 42 New Object Classes Now Available as Map Features
Today we’re announcing 42 new types of map features that Mapillary extracts from street-level imagery and automatically positions onto the map. Ranging from utility poles and streetlights to mailboxes and manholes, this will help cities, mapping companies, and transportation agencies keep their maps up to date using cameras.
2018 Year in Review
2018 is coming to a close, and it’s that time of year where we look back at some of the best moments.
Ramp up Imagery Collection with the New Mapillary Desktop Uploader
The latest addition to the Mapillary toolset is a desktop application that lets you upload thousands of geotagged images with little time and effort.
Announcing Mapillary SDKs: Add Mapillary Capture Functionality to Any Mobile App
The Mapillary mobile app SDKs enable anyone to build a street-level imagery capture component into their app with custom features. This makes it easier and more convenient for people to collect Mapillary imagery, which they can then use to update and enrich maps.
Launching the Better, Faster, Upgraded Mapillary Web
We have just launched an upgraded version of our website that features notable improvements (up to 80%) in page loading times. In addition, we’ve implemented the latest MapillaryJS release which helps straighten up distorted images and make transitions smoother between images. With this, we’re offering a much faster and better experience when using the platform.
Five Years of Mapillary—From the First Image to a Global Platform
This week marks five years since we started this little “project” of ours. It seemed controversial at first but now, five years later, it’s become a completely normal and sane thing. Time for a short reflection on this half-decade.
Improving the Viewing Experience: Image Undistortion in MapillaryJS
Radial distortion is a common problem when the 3D world is represented in 2D images. With the latest MapillaryJS release, we are now undistorting every image. This leads to a better 3D representation and improves the viewing experience of Mapillary images.
Analyzing Parking Signs at Scale: How Mapillary is Working with Amazon Rekognition to Help US Cities End Their Parking Troubles
Managing parking infrastructure is a billion-dollar problem for cities all across the US. There has been no easy way for cities and Departments of Transportation to access parking sign data, resulting in poor decisions around parking infrastructure and planning. Today, Mapillary and Amazon Rekognition are introducing a scalable way to help US cities get a handle of their parking infrastructure.
Announcing the Winners of the Joint COCO and Mapillary Recognition Challenge Workshop for ECCV 2018
Earlier this year, COCO and Mapillary invited computer vision researchers to participate in a workshop co-located with this year’s European Conference on Computer Vision. Today we’re announcing the winners.
Winning the ECCV Semantic Segmentation Challenge for Autonomous Navigation in Unstructured Environments
Mapillary just scored another success in computer vision benchmarking. This wouldn't be possible without our community: by contributing more than 350 million images from all over the world, they've created a dataset that helps build robust algorithms for making sense of any street scene that a self-driving car may encounter.
Celebrating Five Million Kilometers of Mapillary Coverage
At Mapillary, we believe that the best way to visually represent our planet is through people and organizations working together. As of today, our community has collectively mapped five million kilometers!
Extending the Mapillary Vistas Dataset for Perfecting Street Scene Segmentation Models
The newly released extension of the Mapillary Vistas Dataset provides over 60 new object classes and even more granularity, including traffic light states. With a total of more than 150 classes, it remains the most diverse publicly available training dataset covering street scenes from around the world.
Welcoming Till Quack to the Mapillary Team
This week we're happy to welcome Till Quack as Mapillary's first VP of Product
Winning the CVPR Semantic Segmentation Challenge: How Mapillary Makes Computer Vision Algorithms Effective and Robust
Mapillary has won the Semantic Segmentation Challenge as part of the 2018 CVPR Robust Vision Workshop. Here's how we did it.
Launching Mapillary for Organizations: Work Together with the Freshest Map Data
Mapillary now supports organizations to easily create and share street-level imagery and automatically extracted data to keep maps and geospatial datasets up to date.
Simpler Command Line Tools for Everyone
The updated Mapillary command line tools make uploading and preprocessing your imagery easier—and not just for programmers.
More Flexibility to Compare Images with MapillaryJS
After the recent update of MapillaryJS, you can now compare any pair of images, regular as well as panoramas. It also features a simpler design to make MapillaryJS integrate smoothly in various applications.
HERE and Mapillary: Linking Two Global Communities
Our partnership with HERE goes global to reinforce the power of community mapping.
Accurate Privacy Blurring at Scale
We have developed an accurate and fast algorithm for privacy blurring on street-level images. The new model, based on semantic segmentation, detects 99.9% of identifiable faces and license plates and is optimized for large-scale processing.
Scaling up with a $15M Investment
BMW i Ventures, Samsung Catalyst Fund, and NavInfo join our existing investors to support growing the world’s largest collaborative street-level imagery platform for extracting map data using computer vision.
MapillaryJS Now Enables Fast Sequence Navigation
With the recent update of MapillaryJS, we have added controls for fast sequence navigation and better sequence overview. Now you can easily navigate to the beginning, end, or any other position of interest in a sequence.
Mapillary for ArcGIS Pro Enters Public Beta
Mapillary for ArcGIS Pro is now available as a Public Beta with considerable performance improvements compared to the previous version. We invite you to join directly from the Mapillary for ArcGIS page.
Mapillary GIS Meetup—Malmö, 6 Feb
Join us for an evening of GIS talk and demos to learn how street-level imagery can help automatize road and street inventories.
New Benchmarks for Semantic Segmentation Models
Mapillary Research ranks no. 1 for semantic segmentation of street scenes on the Cityscapes and Mapillary Vistas leaderboards.
2017 Year in Review
With another year coming to a close, we’d like to highlight some of its best Mapillary moments.
Boosting Semantic Segmentation Performance with NVIDIA and Amazon
The new NVIDIA Tesla V100 graphics processing units and TensorRT 3.0 library together with Amazon EC2 P3 instances make Mapillary’s semantic segmentation models 27 times faster while using 81% less memory.
Advancing Map Data Extraction with Line Features
We’ve taken a big step forward in extracting map data from images. 19 of the object classes we’re detecting in images via semantic segmentation, all representing line-shaped real-world objects, are now available as line features located on the map.
Added Controls for Sequence Playback: Change Speed and Direction
The latest MapillaryJS release adds support for changing the speed and direction when playing a sequence.
#CompletetheMap—Launching the Global Challenge
After a number a successful local challenges, Complete the Map is going global. To participate in the largest Mapillary challenge, register a location you'd like to contribute to. Kick-off on 11st December!
Introducing the Mapillary Tasker: Collaborate with Anyone on Mapillary
To reinforce the power of collaboration, we made it easier for contributors to work together on clearly defined tasks focused on street-level images. The Mapillary Tasker will let you invite people to help complete capture, map editing, or data verification tasks in your area.
Anyone Can Teach the Computer: The Mapillary Verifier Tool
Today we release a feature for verifying Mapillary’s object detections. The Verifier tool gives anyone the chance to help improve data accuracy while competing in a fun game.
A New Way to Organize Imagery: Introducing Tagging
The tagging feature in Mapillary will let you organize imagery by adding tags to whole images or specific objects in images. As Mapillary in general, this function is also collaborative, so anyone is able to search for tags added by everyone else.
Celebrating 200 Million Images
Thanks to all of you, we've added another hundred million images in less than a year!
Mapillary Partners with Trimble: High-Precision Street-Level Imagery at Your Fingertips
Trimble releases support for Mapillary Exporter to facilitate getting map data from high-quality, high-precision street-level imagery.
Microsoft Donates Imagery to Help with Disaster Recovery in Texas and Florida
To support disaster recovery efforts related to Hurricanes Harvey and Irma, Microsoft is sharing 360° street-level imagery of the affected areas in Texas and Florida to the Mapillary platform.
Visualizing AI Detections for Improved Map Editing
Our new AI detections feature lets you quickly find images where objects have been automatically detected, making it easier to use Mapillary imagery to edit maps and geospatial datasets.
Introducing Mapillary for ArcGIS Pro
Mapillary imagery is now available in ArcGIS Pro. The Beta release of Mapillary for ArcGIS Pro will let you use street-level imagery for visual reference, feature editing, and comparison over time.
Get on the Bus! With OpenStreetMap and Mapillary
Let’s work together to improve the information on bus routes across the US. Join us for the OpenStreetMap US Summer Bus Mapathon!
Street-level Storytelling: Introducing the Mapillary Photostories Tool
Tell your stories in more than words and images! The Mapillary Photostories tool lets you take viewers to the places that matter to you and tell the tales around them.
#CompletetheMap Challenges—Targeted Collection of Fresh Imagery
We're running challenges around the world to create fresh coverage in selected locations and explore the potential for targeted image collection. The goal is to complete the map.
Collaborating to Map the Planet: Extending Our Partnership with HERE
Following a successful pilot, we’re continuing our partnership with HERE, the global map data and location services provider. We’re working with HERE and their Map Creator community to deliver better maps to millions of people—and add millions of images to the Mapillary database along the way.
Mapillary API: Hello to v3 and Goodbye to v2
Here is what you need to know about migrating to Mapillary API v3 as v2 retires.
Pushing the Limits of Scene Understanding: LSUN’17 Workshop and Semantic Image Segmentation Challenges
We invite researchers to participate in a challenge for large-scale scene understanding models as part of the LSUN workshop at this year’s Computer Vision and Pattern Recognition (CVPR) conference.
New iOS Camera Features and Updated User Interface
Mapillary for iOS now lets you capture with the phone's internal camera together with external cameras, and use each camera in any of the three capturing modes (distance- or time-based automatic, or manual mode). In addition, we've added support for more GoPro cameras, and freshened up the camera screen to make it really easy to use the new functions.
Making Digital Mapping Technologies Smarter with an Austrian Research Grant
We are glad to acknowledge that Mapillary Research has received funding from the Austrian Research Promotion Agency (FFG) for building next-generation maps. We have added more computational power and two expert researchers to our Research team to ramp up developing the computer vision algorithms that generate digital map data from Mapillary imagery.
Complete the Map Challenge - Berlin
Over the next three weeks, we’re bringing together the Mapillary community in Berlin in a challenge to photo map zones of Mitte and Kreuzberg. Anyone in Berlin or passing through during this time is welcome to join the
Releasing the World’s Largest Street-level Imagery Dataset for Teaching Machines to See
Mapillary Vistas, the world’s largest and most diverse publicly available, pixel-accurately and instance-specifically annotated street-level imagery dataset, will empower autonomous mobility and transport at the global scale.
Save and Share Your Filter Setups with URLs
You can easily save and share the filters you have set up in the Mapillary viewer, since we now store filters in the URL.
Edit Map Objects with MapillaryJS
The latest MapillaryJS release adds support for map object editing in the viewer.
More Mapillary Partners
We are happy to add three more organizations to our list of partners to help make the most out of street-level imagery.
Find Your Local Vendors on Eniro with Mapillary Street-Level Photos
We're proud to announce that Eniro has integrated Mapillary into their search services, enabling their visitors to find the location of businesses and individuals via street-level images that have been provided by local people.
Street-level Imagery for Appraisals: Partnering with Bruce Harris
We are glad to announce our partnership with Bruce Harris & Associates to make street-level imagery accessible and affordable in appraisal services.
Towards Global Traffic Sign Recognition
We are taking a big step towards recognizing traffic signs all over the world by adding support for more than 500 traffic signs globally, together with an appearance-based taxonomy for traffic signs. This is the beginning of our journey of recognizing every road sign in the world, no matter where it is.
Mapillary for ArcGIS Online v2 Now Available
Improved performance, design and availability—the new Mapillary for ArcGIS Online app is now on the ArcGIS Marketplace.
Are You up for the Challenge? Win an LG 360° Cam
It is time for a Mapillary challenge! Take the chance to win an LG 360° camera by sharing your favourite Mapillary photo sequence with the hashtag #MapillaryExplore.
More Power to Manage Mapillary Resources: Introducing API v3
The API is an important way to make Mapillary useful to developers. Today we are glad to announce the release of Mapillary API v3 that is more simple, powerful, and flexible to use.
Meet Mapillary Ambassadors for 2017
We're happy to introduce you the latest team of Mapillary Ambassadors—15 awesome people that work with our community.
Full Resolution Zoom: View Exactly What You Captured
Our new full resolution zoom feature lets you view every photo in its finest detail and make the most out of high-resolution imagery.
Improved Notifications: Stay on Top of Your Mapillary Activities
You may have noticed that a few things have changed in the Mapillary app. We made it easier for you to get an overview of your Mapillary activities while also providing a deeper understanding of what is going on with each activity.
2016 Year in Review
As we are approaching the end of 2016 I wanted to share some details and stats with you all. 2016 was a great Mapillary year. Here are some of the highlights.
Mapillary Raster Tiles Are Back
Next to vector tiles, we're glad to bring back Mapillary raster tiles to enable better mapping.
Embed Mapillary Street-level Photos Anywhere
Today we are excited to introduce embedding for Mapillary street-level photos. The embed will help you bring Mapillary photos with you anywhere to tell your story.
100 Million Photos - Geotagged, Connected, and Available for All
Last year I wrote a blog post when we hit 10 million photos, to mark the date and thank everyone who helped us get there together. Today, we just passed 100 million.
Faster Navigation: Introducing MapillaryJS 2.0
MapillaryJS 2.0 improves the general performance of retrieving data and decreases the image loading time when navigating to a new place on the map.
Denser 3D Point Clouds in OpenSfM
We've improved OpenSfM—the technology we use to create 3D reconstructions from images. By adding post-processing, we get denser 3D point clouds resulting in better visualization, positioning, and much more.
Time Travel by Mapillary
A couple of weeks ago I went to the Petersen Automotive Museum in Los Angeles to do some research on time travel. After a couple of weeks of work on design and implementation, we arrived at time travel the Mapillary way.
Mapillary for Android—Same Mission, New Beginning
Today we are excited to share a complete makeover of Mapillary for Android with the 3.0 release. Reviewing, uploading and exploring are now much smoother and "more Mapillary", making it really easy to help you create a visual representation of the world.
Your Chance to Shape Our Community: Become a Mapillary Ambassador
We’re happy to announce that the Mapillary Ambassador Programme is expanding. If you feel enthusiastic about Mapillary and want to help grow the community then this is your opportunity.
Mapillary Now Able to Recognize and Label Objects in the Wild
We are happy to announce one of the first new contributions driven by our AI Lab in Graz, Austria - adding a feature that provides semantic segmentations for a select number of object categories. In this blog post, we will discuss what this is all about and why we think that this development will be useful for our members and customers.
Mapillary Joins Berkeley DeepDrive
We’re incredibly excited to join University of California Berkeley’s DeepDrive initiative to help push computer vision and deep learning forward. This, we hope, will improve understanding of street images for safer cities, autonomous cars, and better maps.
Everything is Better in 360: iOS App Gets 360 Support
We have added 360° camera support to the iOS app. The first camera we have added support for is the LG 360 Cam.
State of the Photo Map 2016
Two months ago I wrote a longer update on Mapillary and OpenStreetMap for the State of the Map US conference in Seattle. A lot has happened since, so I wanted to share a short OpenStreetMap-related update in time for State of the Map in Brussels.
Mapillary Named By Fast Company in 2016 Innovation by Design Awards
Big news! We’re finalists in two categories in Fast Company's Innovation By Design Awards 2016.
View What Interests You Most: Introducing Filters
Today we're re-releasing filters from the old Mapillary, sprinkled with a new flavor. If you're not familiar with filtering in general, here is the lowdown.
Partnering With HERE: Community Mapping Pilot
Today we're launching a community mapping pilot with HERE, the global provider of map data and services. We’re excited to welcome fans of MapCreator, HERE’s community tool for editing maps, and hope we can help each other in our mapping projects.
Introducing the Mapillary Humanitarian Mapping Kit, in Partnership with Humanitarian OpenStreetMap Team
Humanitarian OpenStreetMap Team (HOT) does amazing work in building and supporting local mapping communities around the world for people to create their own maps for socio-economic development and disaster preparedness. This is also one of the founding blocks of what we are creating with Mapillary.
Introducing A New, Better Mapillary
Today we’re excited to release the new Mapillary. This major update will improve the experience of exploring places with a redesigned map and a new viewer. We’re also releasing a new editor to edit photos captured by the Mapillary community, as well as improved upload functionality.
The New Mapillary—Design Principles
Redesigning and reimplementing Mapillary turned out to be an unprecedented project in the life of the company, as we basically rebuilt everything from scratch. We started from the ground up: first, we built a new tiler, which allowed us to actually show each photo in a sequence, just like beads on a string. We then asked ourselves if it would be possible to use Mapillary on the full screen map/photo at all times?
Meet Us at State of the Map US 2016!
This week we’re going to State of the Map US in Seattle and we’re looking forward to connect with both old and new friends from this vibrant open community.
Large-scale Map Matching with Meili
This is a joint post by Kevin Kreiser (Mapzen) and Tao Peng (Mapillary).
Mapillary Announced as 2016 Technology Pioneer by World Economic Forum
Our goal at Mapillary is to change the world — at least, to change the way we capture our world and record that representation. So we’re excited to announce this week that we’ve been honored by the World Economic Forum as one of their 2016 Technology Pioneers, a selection of the world’s most innovative early-stage companies.
Mapillary Chrome extension
Mapillary community members have captured and shared millions of photos with the world. You might have seen some spectacular examples on our Instagram and in our newsletters. We'd like to announce a new way to discover great photos on Mapillary in the official Mapillary Chrome extension! Every time you open a new tab you'll see a beautiful photo from Mapillary. You'll also be able to experience walking around these photos thanks to MapillaryJS. Just hit "Explore".
MapillaryEDU: Supporting a New Generation of Mappers
While doing some routine analysis of our photo coverage a few months ago, we noticed some unusual activity in a very specific area in Washington D.C.:
The latest component in a growing list extending the functionality of MapillaryJS exposes an API and functionality for photo tagging. With the tagging component we are adding support for displaying, creating and editing tags.
Say 'Servus' to Our New AI Lab!
Today we're excited to announce our recent addition to the computer vision side of Mapillary. We're opening an office and a deep learning AI lab in Graz, Austria. This is a big step in our quest of understanding places and how these places change over time based on our community's photographs.
Remake of mapillary.com
Did you think that things are slowing down at mapillary.com? Quite the opposite is happening. We're giving our entire site a complete remake.
Support for Multiple Action Cameras
A couple of months ago, we added support for Garmin cameras in the iOS app, and early adopters have shown that it produces amazing photos and sequences. Today we are adding support for multiple Garmin cameras. This means that you can create flexible "camera rigs" so that you can capture more than one direction. With four cameras, you can capture 360 degrees at the same time and don't have to drive the same route as often.
Mapillary and GoPro: Taking Street Photos into the Hands of the Adventurer
We are excited to finally announce that we are part of GoPro's new Developer Program, which was unveiled yesterday at Pier 35 in San Francisco. The program includes more than 100 developers, and we were selected along with 33 other companies to showcase our integration at the launch expo yesterday. It was a busy day showing off how easy our integration lets Mapillary members capture using GoPro cameras. We also met some of the other developers in the program and many GoPro engineers.
Mapillary Joins the US National Park Service’s Centennial Celebration
In 1916, the US National Park Service (NPS) was created to oversee land that had been protected with national park status. Today, the NPS is responsible for more than 84 million acres, which includes areas such as historic sites and monuments, in addition to parks like Yellowstone. This year, the NPS is celebrating its 100th birthday by encouraging people to explore local sites that are part of the National Park System and then share their stories with the #FindYourPark campaign. It’s a beautiful initiative that showcases how the NPS protects areas of all shapes and sizes.
The component based architecture of our open source library MapillaryJS makes it easy to extend with new functionality that is independent from the logic of other elements. Inspired by the historical image comparisons created by @neogeografen we decided to build our own slider component.
Announcing Our $8M Series A Round
We just closed an $8 million Series A financing round to enable us to expand. Last year was an incredible year for our community and for Mapillary as a company but we still have a long way to go to realize our vision of visually mapping the world. With this investment, we are in a great position to go all the way. Atomico led this round, with participation from our previous backers Sequoia, LDV Capital, Playfair, and Wellington.
New Mapillary Ambassadors
We are happy to announce that our Ambassador Program has expanded and we have eight new Ambassadors!
MapillaryJS is a tool used for displaying street level photos anywhere on the internet. Today we are putting it into your hands. It enables you to add street level photos to your blog, website or even into your professional mapping applications. Getting started with MapillaryJS is easy:
Support for more action cameras; GoPro Hero3 and Garmin VirbX/VirbXE
Not long ago, we added support for GoPro® cameras in the iOS app, and early adopters have shown it produces amazing photos and sequences. Now we add support for GoPro® Hero3 as well as Garmin® VirbX/VirbXE and also introduce a high-speed mode using the time-lapse feature of these action cameras.
How Mapillary Works with Cities
At the last Esri User Conference, I met an environmental consultant who worked on a project verifying fire hydrant locations for a small town. He checked out each coordinate on Google Street View -- “by hand!” he insisted, referring to restrictions on using the Google Maps API for deriving datasets and asset tracking. He hadn’t minded the laborious process so much as an unexpected problem: Street View was neither current nor complete. Street View cars had driven through the town over three years ago, and hadn’t captured smaller streets and hiking trails.
Mapillary and GoPro® – A Match Made in Mapping Heaven
We love GoPro® cameras. These tiny action cameras create stunning, quality images. They have a wide field of view and can capture up to two photos every second, making them perfect when you're creating Structure from Motion, like we are with our 3D Navigation tool. Also, they are easy to mount on pretty much anything.
First, there was Picture-in-Picture (PiP). It was awesome and all the kids were raving about it. Now we introduce the next big thing, Map-in-Camera, or simply MiC.
Mapillary Ambassador Program
We are thrilled to announce a new way to engage with the Mapillary community to create a photo representation of the world.
Major Improvements to All Shapes in Mapillary
We have been struggling a long time to get detailed shapes for statistics, notifications and exploration at Mapillary. We have been relying on simplified shapes which were not fully accurate.
Point Clouds: Behind the Scenes of Our 3D Navigation
At Mapillary, we don’t want to simply show you photos on maps – we want you to feel immersed in whichever landscape you’re exploring. Behind-the-scenes, we have been 3D reconstructing every location our members photograph and now, we want to show you. We're giving our community the power to virtually explore their photos like never before.
Panorama Connections and Navigation
Consumer spherical cameras are coming. Some, like the Ricoh Theta, are already here. This means that it is now possible for individuals to capture spherical images massively. Preparing for that, we are now enabling pano navigation mode.
Mapillary Location Search Now Powered by Mapzen Search
Recently Mapzen launched Mapzen Search. It is a search engine for places worldwide, fully powered by open data and freely available to everyone.
Announcing Mapillary for ArcGIS
Today we're pleased to announce the release of Mapillary for ArcGIS!
First Photo Day - A Look at Two Years of Mapillary
Today, October 8, is First Photo Day here at Mapillary, the day when the first Mapillary photo was published in 2013. A lot has happened in these two roller-coaster years. Here is my summary.