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06/15/2021
Scene Transformer: A unified multi-task model for behavior prediction and planning
Predicting the future motion of multiple agents is necessary for plannin...
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04/20/2021
Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset
As autonomous driving systems mature, motion forecasting has received in...
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03/30/2021
3D-MAN: 3D Multi-frame Attention Network for Object Detection
3D object detection is an important module in autonomous driving and rob...
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03/02/2021
Pseudo-labeling for Scalable 3D Object Detection
To safely deploy autonomous vehicles, onboard perception systems must wo...
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10/14/2020
Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout
The vast majority of deep models use multiple gradient signals, typicall...
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05/04/2020
Streaming Object Detection for 3-D Point Clouds
Autonomous vehicles operate in a dynamic environment, where the speed wi...
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04/02/2020
Improving 3D Object Detection through Progressive Population Based Augmentation
Data augmentation has been widely adopted for object detection in 3D poi...
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12/10/2019
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
The research community has increasing interest in autonomous driving res...
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12/10/2019
Scalability in Perception for Autonomous Driving: An Open Dataset Benchmark
The research community has increasing interest in autonomous driving res...
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10/15/2019
End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds
Recent work on 3D object detection advocates point cloud voxelization in...
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08/29/2019
StarNet: Targeted Computation for Object Detection in Point Clouds
LiDAR sensor systems provide high resolution spatial information about t...
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08/28/2019
Learning a Multitask Curriculum for Neural Machine Translation
Existing curriculum learning research in neural machine translation (NMT...
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04/22/2019
Using Videos to Evaluate Image Model Robustness
Human visual systems are robust to a wide range of image transformations...
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04/10/2019
Soft Conditional Computation
Conditional computation aims to increase the size and accuracy of a netw...
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11/16/2018
Domain Adaptive Transfer Learning with Specialist Models
Transfer learning is a widely used method to build high performing compu...
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11/16/2018