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Baidu Apollo Releases Massive Self-driving Dataset; Teams Up With Berkeley DeepDrive

Apollo Scape was released under Baidu's autonomous driving platform Apollo, which Baidu hopes will become “the Android of the auto industry.” Apollo gives developers access to a complete set of service solutions and open-source codes and...

Baidu this Thursday announced the release of Apollo Scape, billed as the world’s largest open-source dataset for autonomous driving technology.

Apollo Scape was released under Baidu’s autonomous driving platform Apollo, which Baidu hopes will become “the Android of the auto industry.” Apollo gives developers access to a complete set of service solutions and open-source codes and can enable for example a software engineer to convert a Lincoln MKZ into a self-driving vehicle in about 48 hours. Apollo Scape’s open sourced data now provides developers a base for building self-driving vehicles.

The data volume of Apollo Scape is 10 times greater than any other open-source autonomous driving dataset, including Kitti and CityScapes. This data can be utilized for perception, simulation scenes, road networks etc., as well as enabling autonomous driving vehicles to be trained in more complex environments, weather and traffic conditions. Apollo Scape also defines 26 different semantic items — eg. cars, bicycles, pedestrians, buildings, streetlights, etc. — with pixel-by-pixel semantic segmentation technique.

The Apollo Scape dataset will save researchers and developers a huge amount of time on real-world sensor data collection.
According to a Rand Corporation report, accumulating sufficient real road testing data to conclude a 20 percent advantage for autonomous vehicles over human drivers would require a fleet of 100 vehicles driving nonstop for 500 years.

Beyond data, Apollo Scape will also faciliate advanced research on cutting-edge simulation technology aiming to create a simulation platform that aligns with real-world experience.

Apollo also announced it has joined the Berkeley DeepDrive (BDD) Industry Consortium, a top-tier research alliance investigating state-of-the-art technologies in computer vision and machine learning for automotive applications.

Housed at the University of California, Berkeley and led by Professor Trevor Darrell, Faculty Director of PATH, the BDD consortium has attracted big tech names as partners, including Ford, Nvidia, Qualcomm, and GM. BDD’s main research focus is on deep reinforcement learning, cross-modal transfer learning, and clockwork FCNs for fast video processing.

Haifeng Wang, Baidu Vice president and Head of Baidu Research Institute, told Synced, “The partnership will incorporate Apollo’s industrial resources and Berkeley’s top academic team to ramp up the innovation of theoretical research, applied technology, and commercial applications.”

Apollo Open Platform and BDD will jointly conduct a Workshop on Autonomous Driving at CVPR 2018 (IEEE International Conference on Computer Vision and Pattern Recognition) this June in Salt Lake City where they will organize task competitions based on Apollo Scape.


Journalist: Tony Peng| Editor: Michael Sarazen

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