activity
20192022
most citedTNT: Target-driveN Trajectory Prediction

211 citations · 471 across the 11 of their papers we have counts for

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12 papers · 1 filter

cs.CV2021

HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps

Lu Mi, Hang Zhao, Charlie Nash +7

High Definition (HD) maps are maps with precise definitions of road lanes with rich semantics of the traffic rules. They are critical for several key stages in an autonomous drivin…

cs.CV2021

To the Point: Efficient 3D Object Detection in the Range Image with Graph Convolution Kernels

Yuning Chai, Pei Sun, Jiquan Ngiam +5

3D object detection is vital for many robotics applications. For tasks where a 2D perspective range image exists, we propose to learn a 3D representation directly from this range i…

cs.CV20217 cited

RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection

Pei Sun, Weiyue Wang, Yuning Chai +5

The detection of 3D objects from LiDAR data is a critical component in most autonomous driving systems. Safe, high speed driving needs larger detection ranges, which are enabled by…

cs.CV2021

Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset

Scott Ettinger, Shuyang Cheng, Benjamin Caine +15

As autonomous driving systems mature, motion forecasting has received increasing attention as a critical requirement for planning. Of particular importance are interactive situatio…

cs.CV20214 cited

Pseudo-labeling for Scalable 3D Object Detection

Benjamin Caine, Rebecca Roelofs, Vijay Vasudevan +4

To safely deploy autonomous vehicles, onboard perception systems must work reliably at high accuracy across a diverse set of environments and geographies. One of the most common te…

cs.CV2020211 cited

TNT: Target-driveN Trajectory Prediction

Hang Zhao, Jiyang Gao, Tian Lan +9

Predicting the future behavior of moving agents is essential for real world applications. It is challenging as the intent of the agent and the corresponding behavior is unknown and…