125 citations · 543 across the 31 of their papers we have counts for
11 papers · 1 filter
Learning to Detect Mobile Objects from LiDAR Scans Without Labels
Yurong You, Katie Z Luo, Cheng Perng Phoo +5
Current 3D object detectors for autonomous driving are almost entirely trained on human-annotated data. Although of high quality, the generation of such data is laborious and costl…
Orientation-Discriminative Feature Representation for Decentralized Pedestrian Tracking
Vikram Shree, Carlos Diaz-Ruiz, Chang Liu +2
This paper focuses on the problem of decentralized pedestrian tracking using a sensor network. Traditional works on pedestrian tracking usually use a centralized framework, which b…
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection
Yurong You, Carlos Andres Diaz-Ruiz, Yan Wang +4
Self-driving cars must detect other vehicles and pedestrians in 3D to plan safe routes and avoid collisions. State-of-the-art 3D object detectors, based on deep learning, have show…
Wasserstein Distances for Stereo Disparity Estimation
Divyansh Garg, Yan Wang, Bharath Hariharan +3
Existing approaches to depth or disparity estimation output a distribution over a set of pre-defined discrete values. This leads to inaccurate results when the true depth or dispar…
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize
Yan Wang, Xiangyu Chen, Yurong You +5
In the domain of autonomous driving, deep learning has substantially improved the 3D object detection accuracy for LiDAR and stereo camera data alike. While deep networks are great…
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection
Rui Qian, Divyansh Garg, Yan Wang +6
Reliable and accurate 3D object detection is a necessity for safe autonomous driving. Although LiDAR sensors can provide accurate 3D point cloud estimates of the environment, they…
An Empirical Study of Person Re-Identification with Attributes
Vikram Shree, Wei-Lun Chao, Mark Campbell
Person re-identification aims to identify a person from an image collection, given one image of that person as the query. There is, however, a plethora of real-life scenarios where…
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving
Yurong You, Yan Wang, Wei-Lun Chao +5
Detecting objects such as cars and pedestrians in 3D plays an indispensable role in autonomous driving. Existing approaches largely rely on expensive LiDAR sensors for accurate dep…
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving
Yan Wang, Wei-Lun Chao, Divyansh Garg +3
3D object detection is an essential task in autonomous driving. Recent techniques excel with highly accurate detection rates, provided the 3D input data is obtained from precise bu…
Deep Person Re-identification for Probabilistic Data Association in Multiple Pedestrian Tracking
Brian H. Wang, Yan Wang, Kilian Q. Weinberger +1
We present a data association method for vision-based multiple pedestrian tracking, using deep convolutional features to distinguish between different people based on their appeara…
Anytime Stereo Image Depth Estimation on Mobile Devices
Yan Wang, Zihang Lai, Gao Huang +4
Many applications of stereo depth estimation in robotics require the generation of accurate disparity maps in real time under significant computational constraints. Current state-o…