Baidu USA LLC

Beijing Baidu Netcom Science and Technology Co., Ltd.

Baidu Online Network Technology (beijing) Co., Ltd.

Jun Zhan

Yu Long Cao

Guang Yu Yang

Yiqing Yang

Siyang Yu

Zhang Li

Xuan Liu

Xu Han

Bryan Catanzaro

Ryan Prenger

Sanjeev Satheesh

Jesse Engel

Erich Elsen

Zhenyao Zhu

Chong Wang

Shubhabrata Sengupta

Christopher Fougner

Awni Hannun

Mike Chrzanowski

Dario Amodei

Jingdong Chen

Dani Yogatama

Houchang Lv

The present application discloses a method and apparatus for annotating point cloud data. A specific implementation of the method includes: collecting data in a given scenario by using a laser radar and a non-laser radar sensor to respectively obtain point cloud data and sensor data; segmenting and tracking the point cloud data to obtain point cloud segmentation and tracking results; recognizing and tracking feature objects in the sensor data to obtain feature object recognition and tracking results; correcting the point cloud segmentation and tracking results by using the feature object recognition and tracking results, to obtain confidence levels of the point cloud recognition and tracking results; and determining a point cloud segmentation and tracking result whose confidence level is greater than a confidence level threshold as a point cloud annotation result. This implementation reduces the amount of manual work required for annotating point cloud data, thereby reducing the annotation costs.

Method and apparatus for annotating point cloud data

Embodiments of the present disclosure disclose a data authentication method, a data authentication apparatus, and a data authentication system. An embodiment of the data authentication method comprises: in response to receiving an authentication request submitted to authentication nodes in an authentication system for authenticating that a vehicle passes self-driving scene testing, verifying the authentication request, the authentication request containing simulation data regarding self-driving testing of the vehicle in a simulated driving scene and authentication award information; in the case of passing the verifying, generating an award record for an authentication node that completes verification first based on the authentication award information, and writing a verification result and the award record into a distributed data block chain corresponding to the authentication system. The embodiment realizes authentication to the driverless vehicle simulation testing data, which may ensure reliability of the authentication result while reducing the time and cost consumed for the authentication.

Self-driving vehicle test authentication

An autonomous driving system includes a number of sensors and a number of autonomous driving modules. The autonomous driving system further includes a global store to store data generated and used by processing modules such as sensors and/or autonomous driving modules. The autonomous driving system further includes a task scheduler coupled to the sensors, the autonomous driving modules, and the global store. In response to output data generated by any one or more of processing modules, the task scheduler stores the output data in the global store. In response to a request from any of the processing modules for processing data, the task scheduler provides input data stored in the global store to the processing module. The task scheduler is executed in a single thread that is responsible for managing data stored in the global store and dispatching tasks to be performed by the processing modules.

Centralized scheduling system for operating autonomous driving vehicles

An event queue is maintained to store IO events generated from a number of sensors and timer events generated for a number of autonomous driving modules. For each of the events pending in the event queue, in response to determining that the event is an IO event, the data associated with the IO event is stored in a data structure associated with the sensor in a global store. In response to determining that the event is a timer event, a worker thread associated with the timer event is launched. The worker thread executes one of the autonomous driving modules triggered or initiated the timer event. Input data is retrieved from the global store and provided to the worker thread to allow the worker thread to process the input data.

Centralized scheduling system using event loop for operating autonomous driving vehicles

A global store is maintained to store a number of data structures. Each data structure includes a number of entries and each entry stores data of at least one event in a chronological order. Each data structure is associated with at least one sensor or an autonomous driving module of an autonomous driving vehicle. When a first event associated with a first autonomous driving module is received, where the first event includes a first topic ID, the first topic ID is hashed to identify a first data structure corresponding to the first event. A pointer pointing to a head of the first data structure is passed to the first autonomous driving module to allow the first autonomous driving module to process data associated with the first event.

Centralized scheduling system using global store for operating autonomous driving vehicles

A method and a system for providing an electronic document, a mother book server and a child book client are provided. The method includes: generating a mother book by a mother book server; receiving, by the mother book server, a request message transmitted by a child book client; generating, by the mother book server, a corresponding child book for the child book client according to the request message and the mother book, and transmitting the child book to the child book client; acquiring, by the child book client, a first position information of a content corresponding to an operation instruction in the mother book, when the child book client receives the operation instruction from a user; and acquiring, by the child book client, the content corresponding to the operation instruction from the mother book server according to the first position information.

Method and system for providing electronic document, mother book server and child book client

Embodiments of end-to-end deep learning systems and methods are disclosed to recognize speech of vastly different languages, such as English or Mandarin Chinese. In embodiments, the entire pipelines of hand-engineered components are replaced with neural networks, and the end-to-end learning allows handling a diverse variety of speech including noisy environments, accents, and different languages. Using a trained embodiment and an embodiment of a batch dispatch technique with GPUs in a data center, an end-to-end deep learning system can be inexpensively deployed in an online setting, delivering low latency when serving users at scale.

End-to-end speech recognition

Deployed end-to-end speech recognition

Described is a system (and method) for generating a driving scenario for an autonomous driving simulator. The system may use a camera mounted to a vehicle as a cost effective approach to obtain real-life driving scenario data. The system may then analyze the two-dimensional image data to create a three-dimensional driving simulation. The analysis may include detecting objects (e.g. vehicles, pedestrians, etc.) within the two-dimensional image data and determining movements of the object based on a position, trajectory, and velocity of the object. The determined information of the object may then be projected onto a map that may be used for generating the three-dimensional driving simulation. The use of cost-effective cameras provides the ability to obtain vast amounts of driving image data that may be used to provide an extensive coverage of the potential types of driving scenarios an autonomous vehicle may encounter.

Vision-based driving scenario generator for autonomous driving simulation

A method for providing an electronic book and a cloud server are provided. The method comprises S: receiving a query; S: performing a search according to the query; and S: generating the electronic book according to a search result responsive to the search.

Method for providing electronic book and cloud server

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Sunnyvale, CA, United States of America

Jun Zhan