Patents by Inventor Namdar Homayounfar
Namdar Homayounfar has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11972606Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain a first type of sensor data (e.g., camera image data) associated with a surrounding environment of an autonomous vehicle and/or a second type of sensor data (e.g., LIDAR data) associated with the surrounding environment of the autonomous vehicle. The computing system can generate overhead image data indicative of at least a portion of the surrounding environment of the autonomous vehicle based at least in part on the first and/or second types of sensor data. The computing system can determine one or more lane boundaries within the surrounding environment of the autonomous vehicle based at least in part on the overhead image data indicative of at least the portion of the surrounding environment of the autonomous vehicle and a machine-learned lane boundary detection model.Type: GrantFiled: May 8, 2023Date of Patent: April 30, 2024Assignee: UATC, LLCInventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrinidihi Kowshika Lakshmikanth, Raquel Urtasun
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Publication number: 20230274540Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain a first type of sensor data (e.g., camera image data) associated with a surrounding environment of an autonomous vehicle and/or a second type of sensor data (e.g., LIDAR data) associated with the surrounding environment of the autonomous vehicle. The computing system can generate overhead image data indicative of at least a portion of the surrounding environment of the autonomous vehicle based at least in part on the first and/or second types of sensor data. The computing system can determine one or more lane boundaries within the surrounding environment of the autonomous vehicle based at least in part on the overhead image data indicative of at least the portion of the surrounding environment of the autonomous vehicle and a machine-learned lane boundary detection model.Type: ApplicationFiled: May 8, 2023Publication date: August 31, 2023Inventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrinidihi Kowshika Lakshmikanth, Raquel Urtasun
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Patent number: 11734828Abstract: Disclosed herein are methods and systems for performing instance segmentation that can provide improved estimation of object boundaries. Implementations can include a machine-learned segmentation model trained to estimate an initial object boundary based on a truncated signed distance function (TSDF) generated by the model. The model can also generate outputs for optimizing the TSDF over a series of iterations to produce a final TSDF that can be used to determine the segmentation mask.Type: GrantFiled: August 1, 2022Date of Patent: August 22, 2023Assignee: UATC, LLCInventors: Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, Raquel Urtasun
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Patent number: 11682196Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain a first type of sensor data (e.g., camera image data) associated with a surrounding environment of an autonomous vehicle and/or a second type of sensor data (e.g., LIDAR data) associated with the surrounding environment of the autonomous vehicle. The computing system can generate overhead image data indicative of at least a portion of the surrounding environment of the autonomous vehicle based at least in part on the first and/or second types of sensor data. The computing system can determine one or more lane boundaries within the surrounding environment of the autonomous vehicle based at least in part on the overhead image data indicative of at least the portion of the surrounding environment of the autonomous vehicle and a machine-learned lane boundary detection model.Type: GrantFiled: June 25, 2021Date of Patent: June 20, 2023Assignee: UATC, LLCInventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrindihi Kowshika Lakshmikanth, Raquel Urtasun
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Patent number: 11562490Abstract: Systems and methods for generating object segmentations across videos are provided. An example system can enable an annotator to identify objects within a first image frame of a video sequence by clicking anywhere within the object. The system processes the first image frame and a second, subsequent, image frame to assign each pixel of the second image frame to one of the objects identified in the first image frame or the background. The system refines the resulting object masks for the second image frame using a recurrent attention module based on contextual features extracted from the second image frame. The system receives additional user input for the second image frame and uses the input, in combination with the object masks for the second image frame, to determine object masks for a third, subsequent, image frame in the video sequence. The process is repeated for each image in the video sequence.Type: GrantFiled: November 17, 2021Date of Patent: January 24, 2023Assignee: UATC, LLCInventors: Namdar Homayounfar, Wei-Chiu Ma, Raquel Urtasun
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Publication number: 20220383505Abstract: Disclosed herein are methods and systems for performing instance segmentation that can provide improved estimation of object boundaries. Implementations can include a machine-learned segmentation model trained to estimate an initial object boundary based on a truncated signed distance function (TSDF) generated by the model. The model can also generate outputs for optimizing the TSDF over a series of iterations to produce a final TSDF that can be used to determine the segmentation mask.Type: ApplicationFiled: August 1, 2022Publication date: December 1, 2022Inventors: Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, Raquel Urtasun
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Patent number: 11410315Abstract: Disclosed herein are methods and systems for performing instance segmentation that can provide improved estimation of object boundaries. Implementations can include a machine-learned segmentation model trained to estimate an initial object boundary based on a truncated signed distance function (TSDF) generated by the model. The model can also generate outputs for optimizing the TSDF over a series of iterations to produce a final TSDF that can be used to determine the segmentation mask.Type: GrantFiled: September 10, 2020Date of Patent: August 9, 2022Assignee: UATC, LLCInventors: Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, Raquel Urtasun
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Publication number: 20220156939Abstract: Systems and methods for generating object segmentations across videos are provided. An example system can enable an annotator to identify objects within a first image frame of a video sequence by clicking anywhere within the object. The system processes the first image frame and a second, subsequent, image frame to assign each pixel of the second image frame to one of the objects identified in the first image frame or the background. The system refines the resulting object masks for the second image frame using a recurrent attention module based on contextual features extracted from the second image frame. The system receives additional user input for the second image frame and uses the input, in combination with the object masks for the second image frame, to determine object masks for a third, subsequent, image frame in the video sequence. The process is repeated for each image in the video sequence.Type: ApplicationFiled: November 17, 2021Publication date: May 19, 2022Inventors: Namdar Homayounfar, Wei-Chiu Ma, Raquel Urtasun
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Publication number: 20210326607Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain a first type of sensor data (e.g., camera image data) associated with a surrounding environment of an autonomous vehicle and/or a second type of sensor data (e.g., LIDAR data) associated with the surrounding environment of the autonomous vehicle. The computing system can generate overhead image data indicative of at least a portion of the surrounding environment of the autonomous vehicle based at least in part on the first and/or second types of sensor data. The computing system can determine one or more lane boundaries within the surrounding environment of the autonomous vehicle based at least in part on the overhead image data indicative of at least the portion of the surrounding environment of the autonomous vehicle and a machine-learned lane boundary detection model.Type: ApplicationFiled: June 25, 2021Publication date: October 21, 2021Inventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrindihi Kowshika Lakshmikanth, Raquel Urtasun
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Patent number: 11080537Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain a first type of sensor data (e.g., camera image data) associated with a surrounding environment of an autonomous vehicle and/or a second type of sensor data (e.g., LIDAR data) associated with the surrounding environment of the autonomous vehicle. The computing system can generate overhead image data indicative of at least a portion of the surrounding environment of the autonomous vehicle based at least in part on the first and/or second types of sensor data. The computing system can determine one or more lane boundaries within the surrounding environment of the autonomous vehicle based at least in part on the overhead image data indicative of at least the portion of the surrounding environment of the autonomous vehicle and a machine-learned lane boundary detection model.Type: GrantFiled: September 5, 2018Date of Patent: August 3, 2021Assignee: UATC, LLCInventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrindihi Kowshika Lakshmikanth, Raquel Urtasun
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Publication number: 20210150410Abstract: Systems and methods for predicting instance geometry are provided. A method includes obtaining an input image depicting at least one object. The method includes determining an instance mask for the object by inputting the input image into a machine-learned instance segmentation model. The method includes determining an initial polygon with a number of initial vertices outlining the border of the object within the input image. The method includes obtaining a feature embedding for one or more pixels of the input image and determining a vertex embedding including a feature embedding for each pixel corresponding an initial vertex of the initial polygon. The method includes determining a vertex offset for each initial vertex of the initial polygon based on the vertex embedding and applying the vertex offset to the initial polygon to obtain one or more enhanced polygons.Type: ApplicationFiled: August 31, 2020Publication date: May 20, 2021Inventors: Justin Liang, Namdar Homayounfar, Wei-Chiu Ma, Yuwen Xiong, Raquel Urtasun
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Publication number: 20210150722Abstract: Disclosed herein are methods and systems for performing instance segmentation that can provide improved estimation of object boundaries. Implementations can include a machine-learned segmentation model trained to estimate an initial object boundary based on a truncated signed distance function (TSDF) generated by the model. The model can also generate outputs for optimizing the TSDF over a series of iterations to produce a final TSDF that can be used to determine the segmentation mask.Type: ApplicationFiled: September 10, 2020Publication date: May 20, 2021Inventors: Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, Raquel Urtasun
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Patent number: 10859384Abstract: Systems and methods for autonomous vehicle localization are provided. In one example embodiment, a computer-implemented method includes obtaining, by a computing system that includes one or more computing devices onboard an autonomous vehicle, sensor data indicative of one or more geographic cues within the surrounding environment of the autonomous vehicle. The method includes obtaining, by the computing system, sparse geographic data associated with the surrounding environment of the autonomous vehicle. The sparse geographic data is indicative of the one or more geographic cues. The method includes determining, by the computing system, a location of the autonomous vehicle within the surrounding environment based at least in part on the sensor data indicative of the one or more geographic cues and the sparse geographic data. The method includes outputting, by the computing system, data indicative of the location of the autonomous vehicle within the surrounding environment.Type: GrantFiled: September 6, 2018Date of Patent: December 8, 2020Assignee: UATC, LLCInventors: Wei-Chiu Ma, Shenlong Wang, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun
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Patent number: 10803325Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain rasterized LIDAR data associated with a surrounding environment of an autonomous vehicle. The rasterized LIDAR data can include LIDAR image data that is rasterized from a LIDAR point cloud. The computing system can access data indicative of a machine-learned lane boundary detection model. The computing system can input the rasterized LIDAR data associated with the surrounding environment of the autonomous vehicle into the machine-learned lane boundary detection model. The computing system can obtain an output from the machine-learned lane boundary detection model. The output can be indicative of one or more lane boundaries within the surrounding environment of the autonomous vehicle.Type: GrantFiled: September 5, 2018Date of Patent: October 13, 2020Assignee: UATC, LLCInventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrindihi Kowshika Lakshmikanth, Raquel Urtasun, Wei-Chiu Ma
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Publication number: 20200302662Abstract: The present disclosure is directed to generating high quality map data using obtained sensor data. In particular a computing system comprising one or more computing devices can obtain sensor data associated with a portion of a travel way. The computing system can identify, using a machine-learned model, feature data associated with one or more lane boundaries in the portion of the travel way based on the obtained sensor data. The computing system can generate a graph representing lane boundaries associated with the portion of the travel way by identifying a respective node location for the respective lane boundary based in part on identified feature data associated with lane boundary information, determining, for the respective node location, an estimated direction value and an estimated lane state, and generating, based on the respective node location, the estimated direction value, and the estimated lane state, a predicted next node location.Type: ApplicationFiled: March 20, 2020Publication date: September 24, 2020Inventors: Namdar Homayounfar, Justin Liang, Wei-Chiu Ma, Raquel Urtasun
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Publication number: 20190147255Abstract: Systems and methods for generating sparse geographic data for autonomous vehicles are provided. In one example embodiment, a computing system can obtain sensor data associated with at least a portion of a surrounding environment of an autonomous vehicle. The computing system can identify a plurality of lane boundaries within the portion of the surrounding environment of the autonomous vehicle based at least in part on the sensor data and a first machine-learned model. The computing system can generate a plurality of polylines indicative of the plurality of lane boundaries based at least in part on a second machine-learned model. Each polyline of the plurality of polylines can be indicative of a lane boundary of the plurality of lane boundaries. The computing system can output a lane graph including the plurality of polylines.Type: ApplicationFiled: September 6, 2018Publication date: May 16, 2019Inventors: Namdar Homayounfar, Wei-Chiu Ma, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun
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Publication number: 20190145784Abstract: Systems and methods for autonomous vehicle localization are provided. In one example embodiment, a computer-implemented method includes obtaining, by a computing system that includes one or more computing devices onboard an autonomous vehicle, sensor data indicative of one or more geographic cues within the surrounding environment of the autonomous vehicle. The method includes obtaining, by the computing system, sparse geographic data associated with the surrounding environment of the autonomous vehicle. The sparse geographic data is indicative of the one or more geographic cues. The method includes determining, by the computing system, a location of the autonomous vehicle within the surrounding environment based at least in part on the sensor data indicative of the one or more geographic cues and the sparse geographic data. The method includes outputting, by the computing system, data indicative of the location of the autonomous vehicle within the surrounding environment.Type: ApplicationFiled: September 6, 2018Publication date: May 16, 2019Inventors: Wei-Chiu Ma, Shenlong Wang, Namdar Homayounfar, Shrinidhi Kowshika Lakshmikanth, Raquel Urtasun
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Publication number: 20190147253Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain rasterized LIDAR data associated with a surrounding environment of an autonomous vehicle. The rasterized LIDAR data can include LIDAR image data that is rasterized from a LIDAR point cloud. The computing system can access data indicative of a machine-learned lane boundary detection model. The computing system can input the rasterized LIDAR data associated with the surrounding environment of the autonomous vehicle into the machine-learned lane boundary detection model. The computing system can obtain an output from the machine-learned lane boundary detection model. The output can be indicative of one or more lane boundaries within the surrounding environment of the autonomous vehicle.Type: ApplicationFiled: September 5, 2018Publication date: May 16, 2019Inventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrindihi Kowshika Lakshmikanth, Raquel Urtasun, Wei-Chiu Ma
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Publication number: 20190147254Abstract: Systems and methods for facilitating communication with autonomous vehicles are provided. In one example embodiment, a computing system can obtain a first type of sensor data (e.g., camera image data) associated with a surrounding environment of an autonomous vehicle and/or a second type of sensor data (e.g., LIDAR data) associated with the surrounding environment of the autonomous vehicle. The computing system can generate overhead image data indicative of at least a portion of the surrounding environment of the autonomous vehicle based at least in part on the first and/or second types of sensor data. The computing system can determine one or more lane boundaries within the surrounding environment of the autonomous vehicle based at least in part on the overhead image data indicative of at least the portion of the surrounding environment of the autonomous vehicle and a machine-learned lane boundary detection model.Type: ApplicationFiled: September 5, 2018Publication date: May 16, 2019Inventors: Min Bai, Gellert Sandor Mattyus, Namdar Homayounfar, Shenlong Wang, Shrindihi Kowshika Lakshmikanth, Raquel Urtasun