Patent Assignment
Reel/Frame 056969/0695
Assignment of Assignor's Interest
Recorded: 2021-03-29
Pages: 16
Assignor
URTASUN SOTIL, RAQUEL
Executed: 2017-04-13
Assignee
UBER TECHNOLOGIES, INC.
1455 MARKET STREET, 4TH FLOOR, SAN FRANCISCO, CALIFORNIA, 94103
Covered Properties
(137)
Probabilistic Prediction of Dynamic Object Behavior for Autonomous Vehicles
Patent:
11,521,396 →
Application:
16/777,108 →
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Application:
62/800,435 →
Probabilistic Prediction of Dynamic Object Behavior for Autonomous Vehicles
Application:
62/949,101 →
Jointly Learnable Behavior and Trajectory Planning for Autonomous Vehicles
Jointly Learnable Behavior and Trajectory Planning for Autonomous Vehicles
Application:
62/955,708 →
Perception and Motion Prediction for Autonomous Devices
PnPNet: Learning Temporal Instance Representations for Joint Perception and Motion Forecasting
Application:
62/822,837 →
Perception and Motion Prediction for Autonomous Devices
Application:
62/942,380 →
System and Methods for Generating High Definition Maps Using Machine-Learned Models to Analyze Topology Data Gathered From Sensors
Application:
16/825,518 →
Publication:
US US20200302662A1
Learning to Map by Discovering Lane Topology
Application:
62/822,841 →
System and Methods for Generating High Definition Maps Using Machine-Learned Models to Analyze Topology Data Gathered From Sensors
Application:
62/942,494 →
Compression of Images Having Overlapping Fields of View Using Machine-Learned Models
Deep Stereo Image Compression
Application:
62/822,842 →
Joint Image Compression Using Machine-Learned Models
Application:
62/969,990 →
Systems and Methods for Generating Synthetic Sensor Data via Machine Learning
LidarSIM: Realistic LiDAR Simulation by Leveraging the Real World
Application:
62/822,844 →
Systems and Methods for Generating Synthetic Light Detection and Ranging Data via Machine Learning
Application:
62/950,279 →
Depth Estimation for Autonomous Devices
Differentiable Deep PatchMatch for Efficient Stereo Matching
Application:
62/822,845 →
Depth Estimation for Autonomous Devices
Application:
62/971,282 →
Systems and Methods for Generating Motion Forecast Data for a Plurality of Actors with Respect to an Autonomous Vehicle
End-to-end Contextual Perception and Prediction with Interaction Transformer
Application:
62/871,436 →
Systems and Methods for Generating Motion Forecast Data For a Plurality of Actors with Respect to an Autonomous Vehicle
Application:
62/930,620 →
Systems and Methods for Generating Motion Forecast Data for Actors with Respect to an Autonomous Vehicle and Training a Machine Learned Model for the Same
SpAGNN: Spatialy-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data
Application:
62/871,452 →
Systems and Methods for Generating Motion Forecast Data for Actors with Respect to an Autonomous Vehicle and Training a Machine Learned Model for the Same
Application:
62/926,826 →
Systems and Methods for Identifying Unknown Instances
Identifying Unknown Instances for Autonomous Driving
Application:
62/871,458 →
Systems and Methods for Identifying Unknown Instances
Application:
62/925,288 →
Systems and Methods for Training Object Detection Models Using Adversarial Examples
Towards Physically Realistic Adversarial Examples for LiDAR Object Detection
Application:
62/936,421 →
Systems and Methods for Training Object Detection Models Using Adversarial Examples
Application:
63/021,942 →
Systems and Methods for Answering Region Specific Questions
Universal Spatial Embeddings for Question Answering in Self-Driving
Application:
62/936,425 →
Systems and Methods for Answering Region Specific Questions
Application:
63/020,166 →
Localization with Diverse Dataset for Autonomous Vehicles
Global Localization in the Age of Self-Driving Cars
Application:
62/936,434 →
Localization with Diverse Dataset for Autonomous Vehicles
Application:
63/027,542 →
Systems and Methods for Predicting Instance Geometry
Application:
17/007,667 →
Publication:
US US20210150410A1
PolyTransform: Deep Polygon Transformer for Instance Segmentation
Application:
62/936,450 →
Systems and Methods for Predicting Instance Geometry
Application:
63/021,943 →
Object Trajectory Evolution for End-to-End Perception and Prediction
Application:
62/936,423 →
LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World
Application:
62/936,439 →
Systems and Methods for Vehicle-to-Vehicle Communications for Improved Autonomous Vehicle Operations
Systems and Methods for Vehicle-to-Vehicle Communications for Improved Autonomous Vehicle Operations
Systems and Methods for Vehicle-to-Vehicle Communications for Improved Autonomous Vehicle Operations
V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction
Application:
62/936,436 →
Systems and Methods for Vehicle-to-Vehicle Communications for Improved Autonomous Vehicle Operations
Application:
63/034,152 →
Conditional Entropy Coding for Efficient Video Compression
Conditional Entropy Coding for Efficient Video Compression
Application:
62/936,431 →
Conditional Entropy Coding for Efficient Video Compression
Application:
63/026,252 →
Systems and Methods for Generating Motion Forecast Data for a Plurality of Actors with Respect to an Autonomous Vehicle
End-to-End Contextual Perception and Prediction with Interaction Transformer
Application:
62/936,438 →
Systems and Methods for Generating Motion Forecast Data for a Plurality of Actors with Respect to an Autonomous Vehicle
Application:
63/022,806 →
Systems and Methods for Jointly Performing Perception, Perception, and Motion Planning for an Autonomous System
Application:
17/022,923 →
Publication:
US US20210149404A1
DSDNet: End-to-End Deep Structured Self-Driving Network
Application:
62/936,415 →
System and Methods for Jointly Performing Perception, Perception, and Motion Planning for an Autonomous System
Application:
63/033,361 →
High Quality Instance Segmentation
LevelSet R-CNN
Application:
62/936,448 →
High Quality Instance Segmentation
Application:
63/024,847 →
System and Methods for Encoding Octree Structured Point Cloud Data Using an Entropy Model
OctSqueeze: Octree-Structured Entropy Model for LiDAR Compression
Application:
62/936,428 →
System And Methods for Encoding Octree Structured Point Cloud Data Using an Entropy Model
Application:
63/022,014 →
Systems and Methods for Optimized Multi-Agent Routing Between Nodes
Application:
17/032,509 →
Publication:
US US20210248460A1
Multi-Agent Routing Value Iteration Network
Application:
62/971,422 →
Systems and Methods for Optimized Multi-Agent Routing Between Nodes
Application:
63/023,483 →
Systems and Methods for Training Probabilistic Object Motion Prediction Models Using Non-Differentiable Prior Knowledge
Precise Multimodal Prediction with Prior Knowledge
Application:
62/984,034 →
Systems and Methods for Training Probabilistic Object Motion Prediction Models Using Non-Differentiable Prior Knowledge
Application:
63/123,251 →
Systems and Methods for Using Attention Masks to Improve Motion Planning
Perceive, Attend and Drive: Learning Spatial Attention for Safe Self-Driving
Application:
62/985,848 →
Systems and Methods for Using Attention Masks to Improve Motion Planning
Application:
63/132,967 →
Systems and Methods for Autonomous Vehicle Systems Simulation
Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction
Application:
62/985,844 →
Systems and Methods for Integrating Radar Data for Improved Object Detection in Autonomous Vehicles
RadarNet: Exploiting Radar for Autonomous Vehicle Perception
Application:
62/985,855 →
Systems and Methods for Integrating Radar Data for Improved Object Detection in Autonomous Vehicles
Application:
63/133,000 →
Systems and Methods for Training Machine-Learned Models with Deviating Intermediate Representations
Adversarial Attacks On Multi-Agent Deep Learning Systems
Application:
62/985,865 →
Systems and Methods for Training Machine-Learned Models with Deviating Intermediate Representations
Application:
63/132,780 →
Systems and Methods for Latent Distribution Modeling for Scene-Consistent Motion Forecasting
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting
Application:
62/985,862 →
Systems and Methods for Latent Distribution Modeling for Scene-Consistent Motion Forecasting
Application:
63/119,981 →
Systems and Methods for Selecting Trajectories Based on Interpretable Semantic Representations
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations
Application:
62/985,847 →
Universal Spatial Embeddings for Structured Question Answering in Self-Driving
Application:
62/985,863 →
MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models
Application:
63/035,571 →
Photorealistic Image Simulation with Geometry-Aware Composition
GeoSim: Photorealistic Image Simulation with Geometry-Aware Composition for Self-Driving
Application:
63/035,573 →
Learning Dynamic Object Removal in the Wild via Geometry-aware Multi-modal Representations
Application:
63/035,577 →
Systems and Methods for Mitigating Vehicle Pose Error Across an Aggregated Feature Map
Learning to Communicate and Correct Pose Errors
Application:
63/058,040 →
Systems and Methods for Mitigating Vehicle Pose Error Across an Aggregated Feature Map
Application:
63/132,792 →
Recovering and Simulating Pedestrians in the Wild
Application:
63/058,052 →
On the Compression of Deep Neural Networks using Vector Quantization
Application:
63/058,041 →
StrObe: Streaming Object Detection from LiDAR Packets
Application:
63/058,043 →
Asynchronous Multi-View SLAM
Application:
63/107,806 →
Joint Structured Model for Reactive Prediction and Planning
Application:
63/108,340 →
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles
Application:
63/114,782 →
TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors
Application:
63/114,862 →
Auto4D: Learning to Label 4D Objects from Sequential Point Clouds
Application:
63/114,785 →
SceneGen: Learning to Simulate Realistic Traffic Scenes
Application:
63/114,848 →
VideoClick: Video Object Segmentation with a Single Click
Application:
63/114,811 →
LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting
Application:
63/114,855 →
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving
Application:
63/114,790 →
Continuous Convolution and Fusion in Neural Networks
Three-Dimensional Object Detection
Three-Dimensional Object Detection
Exploiting Continuous Convolutions for 3D Object Detection with Multisensor Fusion
Application:
62/643,072 →
Three-Dimensional Object Detection
Application:
62/753,434 →
Exploiting Hd Maps for 3D Object Detection
Application:
62/685,871 →
Multi-Task Machine-Learned Models for Object Intention Determination in Autonomous Driving
Multi-Task Machine-Learned Models For Object Intention Determination in Autonomous Driving
Application:
62/748,057 →
System and Method for Determining Object Intention Through Visual Attributes
System and Method for Determining Object Intention through Visual Attributes
Application:
62/754,942 →
Systems and Methods for Generating Synthetic Light Detection and Ranging Data via Machine Learning
LidarSIM: Combining Physics and Deep Learning for LiDAR Simulation
Application:
62/768,850 →
Systems and Methods for Generating Synthetic Light Detection and Ranging Data Via Machine Learning
Application:
62/834,596 →
Image Based Localization System
Image Based Localization System
Application:
62/829,672 →
Feature Compression and Localization for Autonomous Devices
Binary Feature Compression for Autonomous Devices
Attention Based Feature Compression and Localization for Autonomous Devices
Learning to Localize through Compressed Binary Maps
Application:
62/768,816 →
Feature Compression and Localization for Autonomous Devices
Application:
62/846,248 →
Learning to Match with Deep Structured Attention
Application:
62/768,849 →
Deep Structured Scene Flow for Autonomous Devices
Deep Structured Scene Flow
Application:
62/768,774 →
Deep Structured Scene Flow for Autonomous Devices
Application:
62/851,753 →
System and Method for Identifying Travel Way Features for Autonomous Vehicle Motion Control
Non-Parametric Memory for Spatio-Temporal Segmentation
Application:
62/768,829 →
System And Method For Identifying Travel Way Features for Autonomous Vehicle Motion Control
Application:
62/869,251 →
Multi-Task Multi-Sensor Fusion for Three-Dimensional Object Detection
Multi-Task Multi-Sensor Fusion for 3D Object Detection
Application:
62/768,790 →
Multi-Task Multi-Sensor Fusion for Three-Dimensional Object Detection
Application:
62/858,489 →
End-To-End Interpretable Motion Planner for Autonomous Vehicles
End-to-end Interpretable Neural Motion Planner
Application:
62/768,847 →
Related Assignments
(25)
Other recorded transfers of the patents in this record — the chain of ownership.
Change of Name
Sep 12, 2019
From: UBER TECHNOLOGIES, INC.
To: UATC, LLC
Reel/Frame 050353/0588 →
Corrective Assignment to Correct the Nature of Conveyance from Change of Name to Assignment Previously Recorded on Reel 050353 Frame 0588. Assignor(S) Hereby Confirms the Nature of Conveyance Should Be Assignment.
Nov 27, 2019
From: UBER TECHNOLOGIES, INC.
To: UATC, LLC
Reel/Frame 051142/0802 →
Assignment of Assignor's Interest
Dec 2, 2020
From: UBER TECHNOLOGIES, INC.
To: UATC, LLC
Reel/Frame 054637/0041 →
Assignment of Assignor's Interest
Dec 18, 2020
From: LIANG, JUSTIN
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054696/0965 →
Assignment of Assignor's Interest
Dec 18, 2020
From: UATC, LLC
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054805/0001 →
Assignment of Assignor's Interest
Dec 18, 2020
From: CHEN, YUN
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054696/0755 →
Assignment of Assignor's Interest
Dec 18, 2020
From: WANG, SHENLONG
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054697/0048 →
Assignment of Assignor's Interest
Dec 20, 2020
From: CASAS, SERGIO
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054703/0325 →
Assignment of Assignor's Interest
Dec 20, 2020
From: YEN, MENGYE
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054703/0316 →
Assignment of Assignor's Interest
Dec 20, 2020
From: MA, WEI-CHIU
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054703/0299 →
Assignment of Assignor's Interest
Dec 20, 2020
From: REN, MENGYE
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054703/0334 →
Assignment of Assignor's Interest
Dec 20, 2020
From: MA, WEI-CHIU
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054703/0293 →
Assignment of Assignor's Interest
Jan 8, 2021
From: UBER TECHNOLOGIES, INC.
To: UATC, LLC
Reel/Frame 054940/0279 →
Corrective Assignment to Correct the Inventor Last Name Previously Recorded at Reel: 054703 Frame: 0316. Assignor(S) Hereby Confirms the Assignment.
Jan 8, 2021
From: REN, MENGYE
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054941/0593 →
Assignment of Assignor's Interest
Jan 14, 2021
From: SADAT, ABBAS; REN, MENGYE; LIN, YEN-CHEN; YUMER, ERSIN
To: UATC, LLC
Reel/Frame 054925/0711 →
Assignment of Assignor's Interest
Jan 14, 2021
From: SADAT, ABBAS; REN, MENGYE; LIN, YEN-CHEN; YUMER, ERSIN
To: UATC, LLC
Reel/Frame 054925/0254 →
Assignment of Assignor's Interest
Jan 14, 2021
From: JAIN, AJAY; CASAS, SERGIO; LIAO, RENJIE; XIONG, YUWEN
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054924/0850 →
Assignment of Assignor's Interest
Jan 14, 2021
From: JAIN, AJAY; CASAS, SERGIO; LIAO, RENJIE; XIONG, YUWEN
To: UATC, LLC
Reel/Frame 054924/0715 →
Assignment of Assignor's Interest
Jan 14, 2021
From: JAIN, AJAY; CASAS, SERGIO; LIAO, RENJIE; XIONG, YUWEN
To: UATC, LLC
Reel/Frame 054914/0638 →
Assignment of Assignor's Interest
Jan 15, 2021
From: HOMAYOUNFAR, NAMDAR; MA, WEI-CHIU
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054938/0856 →
Assignment of Assignor's Interest
Jan 15, 2021
From: HOMAYOUNFAR, NAMDAR; LIANG, JUSTIN; MA, WEI-CHIU
To: UATC, LLC
Reel/Frame 054938/0844 →
Assignment of Assignor's Interest
Jan 15, 2021
From: YANG, BIN; CHEN, YUN
To: UATC, LLC
Reel/Frame 054936/0018 →
Assignment of Assignor's Interest
Jan 15, 2021
From: YANG, BIN
To: UBER TECHNOLOGIES, INC.
Reel/Frame 054935/0986 →
Assignment of Assignor's Interest
Jan 15, 2021
From: YANG, BIN; CHEN, YUN
To: UATC, LLC
Reel/Frame 054935/0881 →
Assignment of Assignor's Interest
Jan 15, 2021
From: LIU, JERRY JUNKAI; WANG, SHENLONG
To: UATC, LLC
Reel/Frame 054938/0886 →