We’re releasing this dataset publicly to aid the research community in making advancements in machine perception and self-driving technology.To read more about the dataset and access it, please visit This code repository (excluding third_party) is licensed under the Apache License, Version 2.0. (2019). Table2contains detailed specifications of our LiDAR data.

Sensor Specifications The data collection was conducted using five LiDAR sen-sors and five high-resolution pinhole cameras. The Waymo Open Dataset is comprised of high resolution sensor data collected by Waymo self-driving cars in a wide variety of conditions. Waymo is in a unique position to contribute to the research community with one of the largest and most diverse autonomous driving datasets ever released. We believe it is one of the largest, richest, and most diverse self-driving datasets ever released for … Files for waymo-open-dataset, version 1.0.1; Filename, size File type Python version Upload date Hashes; Filename, size waymo_open_dataset-1.0.1-cp27-cp27mu-manylinux2010_x86_64.whl (2.7 MB) File type Wheel Python version cp27 Upload date Sep 6, 2019

We plan to grow this dataset in the future. Our tracking algorithms are evaluated on the Waymo Open Dataset v1.2 [7]. g++ 5 or higher. This Quick Start contains installation instructions for the Open Dataset codebase. Here is what is currently included:This data is licensed for non-commercial use.

Notably, our overall detection system achieves 70.28 L2 mAP on the Waymo Open Dataset v1.2, ranking the 2nd place in the 2D detection track of the Waymo Open Dataset Challenges. In this report, we introduce a state-of-the-art 2D object detection system for autonomous driving scenarios. Check out the Challenges page for more details. The Waymo Open Dataset is comprised of high-resolution sensor data collected by Waymo self-driving cars in a wide variety of conditions. The collection is comprised of different times including sunshine, rain, day, night, dawn and dusk. Leaderboards are open! Leaderboards are open! Dataset. A practical autonomous driving system urges the need to reliably and accurately detect vehicles and persons. The Waymo Open Dataset also improves on data diversity, factoring in variables such as weather, pedestrians, lighting conditions, cyclists and construction.

We restrict the range of the LiDAR data, and provide data for the first two returns of each laser pulse. Our new dataset consists of 1150 scenes that each span 20 seconds, consisting of well synchronized and calibrated high quality LiDAR and camera data captured across a range of urban and suburban geographies.

We are releasing this dataset publicly to aid the research community in making advancements in machine perception and self-driving technology.The Waymo Open Dataset currently contains 1,950 segments. ∙ 0 ∙ share The research community has increasing interest in autonomous driving research, despite the resource intensity of obtaining representative real world data. Specifically, we integrate both popular two-stage detector and one-stage detector with anchor free fashion to yield a robust detection. ∙ 0 ∙ share Sijia Chen, et al.

06/28/2020 ∙ by Sijia Chen, et al. Please visit The following table is necessary for this dataset to be indexed by search

In March 2020, we launched the Waymo Open Dataset Challenges, inviting researchers to build and test their machine learning models using Waymo’s diverse self-driving dataset.We received over 100 submissions from around the world and invited the winners to present their work at our virtual Workshop on Scalability in Autonomous Driving at CVPR 2020. The Waymo Open Dataset challenges attracted many participants in the field of computer vision and autonomous driving. Yesterday, Waymo open-sourced high-quality multimodal sensor dataset for autonomous driving. You can find the license agreement While this dataset is not reflective of the full capabilities of our sensor system and is only a fraction of the data on which Waymo’s self-driving system is trained, we believe that for research purposes this large, diverse and high-quality dataset is extremely valuable.

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