229 citations · 965 across the 30 of their papers we have counts for
31 papers
What Happened 3 Seconds Ago? Inferring the Past with Thermal Imaging
Zitian Tang, Wenjie Ye, Wei-Chiu Ma +1
Inferring past human motion from RGB images is challenging due to the inherent uncertainty of the prediction problem. Thermal images, on the other hand, encode traces of past human…
AsyInst: Asymmetric Affinity with DepthGrad and Color for Box-Supervised Instance Segmentation
Siwei Yang, Longlong Jing, Junfei Xiao +3
The weakly supervised instance segmentation is a challenging task. The existing methods typically use bounding boxes as supervision and optimize the network with a regularization l…
Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking
Longlong Jing, Ruichi Yu, Henrik Kretzschmar +11
Monocular image-based 3D perception has become an active research area in recent years owing to its applications in autonomous driving. Approaches to monocular 3D perception includ…
VectorMapNet: End-to-end Vectorized HD Map Learning
Yicheng Liu, Tianyuan Yuan, Yue Wang +2
Autonomous driving systems require High-Definition (HD) semantic maps to navigate around urban roads. Existing solutions approach the semantic mapping problem by offline manual ann…
M2I: From Factored Marginal Trajectory Prediction to Interactive Prediction
Qiao Sun, Xin Huang, Junru Gu +2
Predicting future motions of road participants is an important task for driving autonomously in urban scenes. Existing models excel at predicting marginal trajectories for single a…
SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-Training for Spatial-Aware Visual Representations
Zhenyu Li, Zehui Chen, Ang Li +6
Pre-training has become a standard paradigm in many computer vision tasks. However, most of the methods are generally designed on the RGB image domain. Due to the discrepancy betwe…
AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detection
Zehui Chen, Zhenyu Li, Shiquan Zhang +5
Object detection through either RGB images or the LiDAR point clouds has been extensively explored in autonomous driving. However, it remains challenging to make these two data sou…
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…
Unsupervised Monocular Depth Learning in Dynamic Scenes
Hanhan Li, Ariel Gordon, Hang Zhao +2
We present a method for jointly training the estimation of depth, ego-motion, and a dense 3D translation field of objects relative to the scene, with monocular photometric consiste…
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…
Online 3D Bin Packing with Constrained Deep Reinforcement Learning
Hang Zhao, Qijin She, Chenyang Zhu +2
We solve a challenging yet practically useful variant of 3D Bin Packing Problem (3D-BPP). In our problem, the agent has limited information about the items to be packed into the bi…
VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation
Jiyang Gao, Chen Sun, Hang Zhao +4
Behavior prediction in dynamic, multi-agent systems is an important problem in the context of self-driving cars, due to the complex representations and interactions of road compone…
Music Gesture for Visual Sound Separation
Chuang Gan, Deng Huang, Hang Zhao +2
Recent deep learning approaches have achieved impressive performance on visual sound separation tasks. However, these approaches are mostly built on appearance and optical flow lik…
AlignNet: A Unifying Approach to Audio-Visual Alignment
Jianren Wang, Zhaoyuan Fang, Hang Zhao
We present AlignNet, a model that synchronizes videos with reference audios under non-uniform and irregular misalignments. AlignNet learns the end-to-end dense correspondence betwe…
Scalability in Perception for Autonomous Driving: Waymo Open Dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla +22
The research community has increasing interest in autonomous driving research, despite the resource intensity of obtaining representative real world data. Existing self-driving dat…
Self-supervised Moving Vehicle Tracking with Stereo Sound
Chuang Gan, Hang Zhao, Peihao Chen +2
Humans are able to localize objects in the environment using both visual and auditory cues, integrating information from multiple modalities into a common reference frame. We intro…