359 citations · 635 across the 21 of their papers we have counts for
21 papers
LDMapNet-U: An End-to-End System for City-Scale Lane-Level Map Updating
Deguo Xia, Weiming Zhang, Xiyan Liu +6
An up-to-date city-scale lane-level map is an indispensable infrastructure and a key enabling technology for ensuring the safety and user experience of autonomous driving systems.…
MONOPOLY: Learning to Price Public Facilities for Revaluing Private Properties with Large-Scale Urban Data
Miao Fan, Jizhou Huang, An Zhuo +3
The value assessment of private properties is an attractive but challenging task which is widely concerned by a majority of people around the world. A prolonged topic among us is `…
DuMapper: Towards Automatic Verification of Large-Scale POIs with Street Views at Baidu Maps
Miao Fan, Jizhou Huang, Haifeng Wang
With the increased popularity of mobile devices, Web mapping services have become an indispensable tool in our daily lives. To provide user-satisfied services, such as location sea…
HGAMN: Heterogeneous Graph Attention Matching Network for Multilingual POI Retrieval at Baidu Maps
Jizhou Huang, Haifeng Wang, Yibo Sun +4
The increasing interest in international travel has raised the demand of retrieving point of interests in multiple languages. This is even superior to find local venues such as res…
Exploring the Causality of End-to-End Autonomous Driving
Jiankun Li, Hao Li, Jiangjiang Liu +6
Deep learning-based models are widely deployed in autonomous driving areas, especially the increasingly noticed end-to-end solutions. However, the black-box property of these model…
BEVWorld: A Multimodal World Simulator for Autonomous Driving via Scene-Level BEV Latents
Yumeng Zhang, Shi Gong, Kaixin Xiong +7
World models have attracted increasing attention in autonomous driving for their ability to forecast potential future scenarios. In this paper, we propose BEVWorld, a novel framewo…
DuMapNet: An End-to-End Vectorization System for City-Scale Lane-Level Map Generation
Deguo Xia, Weiming Zhang, Xiyan Liu +5
Generating city-scale lane-level maps faces significant challenges due to the intricate urban environments, such as blurred or absent lane markings. Additionally, a standard lane-l…
Spatial Heterophily Aware Graph Neural Networks
Congxi Xiao, Jingbo Zhou, Jizhou Huang +2
Graph Neural Networks (GNNs) have been broadly applied in many urban applications upon formulating a city as an urban graph whose nodes are urban objects like regions or points of…
A Contextual Master-Slave Framework on Urban Region Graph for Urban Village Detection
Congxi Xiao, Jingbo Zhou, Jizhou Huang +4
Urban villages (UVs) refer to the underdeveloped informal settlement falling behind the rapid urbanization in a city. Since there are high levels of social inequality and social ri…
DuETA: Traffic Congestion Propagation Pattern Modeling via Efficient Graph Learning for ETA Prediction at Baidu Maps
Jizhou Huang, Zhengjie Huang, Xiaomin Fang +5
Estimated time of arrival (ETA) prediction, also known as travel time estimation, is a fundamental task for a wide range of intelligent transportation applications, such as navigat…
ERNIE-GeoL: A Geography-and-Language Pre-trained Model and its Applications in Baidu Maps
Jizhou Huang, Haifeng Wang, Yibo Sun +4
Pre-trained models (PTMs) have become a fundamental backbone for downstream tasks in natural language processing and computer vision. Despite initial gains that were obtained by ap…
Understanding the Impact of the COVID-19 Pandemic on Transportation-related Behaviors with Human Mobility Data
Jizhou Huang, Haifeng Wang, Miao Fan +3
The constrained outbreak of COVID-19 in Mainland China has recently been regarded as a successful example of fighting this highly contagious virus. Both the short period (in about…
Adversarial Neural Trip Recommendation
Linlang Jiang, Jingbo Zhou, Tong Xu +4
Trip recommender system, which targets at recommending a trip consisting of several ordered Points of Interest (POIs), has long been treated as an important application for many lo…
GEDIT: Geographic-Enhanced and Dependency-Guided Tagging for Joint POI and Accessibility Extraction at Baidu Maps
Yibo Sun, Jizhou Huang, Chunyuan Yuan +4
Providing timely accessibility reminders of a point-of-interest (POI) plays a vital role in improving user satisfaction of finding places and making visiting decisions. However, it…
DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features
Min Yang, Dongliang He, Miao Fan +5
Image Retrieval is a fundamental task of obtaining images similar to the query one from a database. A common image retrieval practice is to firstly retrieve candidate images via si…
From Distributed Machine Learning to Federated Learning: A Survey
Ji Liu, Jizhou Huang, Yang Zhou +4
In recent years, data and computing resources are typically distributed in the devices of end users, various regions or organizations. Because of laws or regulations, the distribut…
Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve Backbones
Cheng Cui, Ruoyu Guo, Yuning Du +10
Recently, research efforts have been concentrated on revealing how pre-trained model makes a difference in neural network performance. Self-supervision and semi-supervised learning…
C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak
Congxi Xiao, Jingbo Zhou, Jizhou Huang +4
The novel coronavirus disease (COVID-19) has crushed daily routines and is still rampaging through the world. Existing solution for nonpharmaceutical interventions usually needs to…
An Investigation of Containment Measures Against the COVID-19 Pandemic in Mainland China
Ji Liu, Xiakai Wang, Haoyi Xiong +5
As the recent COVID-19 outbreak rapidly expands all over the world, various containment measures have been carried out to fight against the COVID-19 pandemic. In Mainland China, th…
Quantifying the Economic Impact of COVID-19 in Mainland China Using Human Mobility Data
Jizhou Huang, Haifeng Wang, Haoyi Xiong +4
To contain the pandemic of coronavirus (COVID-19) in Mainland China, the authorities have put in place a series of measures, including quarantines, social distancing, and travel re…
Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos
Dongliang He, Xiang Zhao, Jizhou Huang +3
The task of video grounding, which temporally localizes a natural language description in a video, plays an important role in understanding videos. Existing studies have adopted st…