229 citations · 965 across the 30 of their papers we have counts for
9 papers · 1 filter
Embracing Single Stride 3D Object Detector with Sparse Transformer
Lue Fan, Ziqi Pang, Tianyuan Zhang +5
In LiDAR-based 3D object detection for autonomous driving, the ratio of the object size to input scene size is significantly smaller compared to 2D detection cases. Overlooking thi…
IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenes
Qi Li, Kaichun Mo, Yanchao Yang +2
Building embodied intelligent agents that can interact with 3D indoor environments has received increasing research attention in recent years. While most works focus on single-obje…
DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries
Yue Wang, Vitor Guizilini, Tianyuan Zhang +3
We introduce a framework for multi-camera 3D object detection. In contrast to existing works, which estimate 3D bounding boxes directly from monocular images or use depth predictio…
Learning Practically Feasible Policies for Online 3D Bin Packing
Hang Zhao, Chenyang Zhu, Xin Xu +2
We tackle the Online 3D Bin Packing Problem, a challenging yet practically useful variant of the classical Bin Packing Problem. In this problem, the items are delivered to the agen…
DenseTNT: End-to-end Trajectory Prediction from Dense Goal Sets
Junru Gu, Chen Sun, Hang Zhao
Due to the stochasticity of human behaviors, predicting the future trajectories of road agents is challenging for autonomous driving. Recently, goal-based multi-trajectory predicti…
HDMapNet: An Online HD Map Construction and Evaluation Framework
Qi Li, Yue Wang, Yilun Wang +1
Constructing HD semantic maps is a central component of autonomous driving. However, traditional pipelines require a vast amount of human efforts and resources in annotating and ma…
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…
DenseTNT: Waymo Open Dataset Motion Prediction Challenge 1st Place Solution
Junru Gu, Qiao Sun, Hang Zhao
In autonomous driving, goal-based multi-trajectory prediction methods are proved to be effective recently, where they first score goal candidates, then select a final set of goals,…
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…