75 citations · 183 across the 19 of their papers we have counts for
24 papers
Detection of Active Emergency Vehicles using Per-Frame CNNs and Output Smoothing
Meng Fan, Craig Bidstrup, Zhaoen Su +3
While inferring common actor states (such as position or velocity) is an important and well-explored task of the perception system aboard a self-driving vehicle (SDV), it may not a…
Convolutions for Spatial Interaction Modeling
Zhaoen Su, Chao Wang, David Bradley +3
In many different fields interactions between objects play a critical role in determining their behavior. Graph neural networks (GNNs) have emerged as a powerful tool for modeling…
Investigating the Effect of Sensor Modalities in Multi-Sensor Detection-Prediction Models
Abhishek Mohta, Fang-Chieh Chou, Brian C. Becker +2
Detection of surrounding objects and their motion prediction are critical components of a self-driving system. Recently proposed models that jointly address these tasks rely on a n…
Uncertainty-Aware Vehicle Orientation Estimation for Joint Detection-Prediction Models
Henggang Cui, Fang-Chieh Chou, Jake Charland +2
Object detection is a critical component of a self-driving system, tasked with inferring the current states of the surrounding traffic actors. While there exist a number of studies…
Ellipse Loss for Scene-Compliant Motion Prediction
Henggang Cui, Hoda Shajari, Sai Yalamanchi +1
Motion prediction is a critical part of self-driving technology, responsible for inferring future behavior of traffic actors in autonomous vehicle's surroundings. In order to ensur…
Temporally-Continuous Probabilistic Prediction using Polynomial Trajectory Parameterization
Zhaoen Su, Chao Wang, Henggang Cui +3
A commonly-used representation for motion prediction of actors is a sequence of waypoints (comprising positions and orientations) for each actor at discrete future time-points. Whi…
Multi-Modal Trajectory Prediction of NBA Players
Sandro Hauri, Nemanja Djuric, Vladan Radosavljevic +1
National Basketball Association (NBA) players are highly motivated and skilled experts that solve complex decision making problems at every time point during a game. As a step towa…
Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving
Sudeep Fadadu, Shreyash Pandey, Darshan Hegde +4
We present an end-to-end method for object detection and trajectory prediction utilizing multi-view representations of LiDAR returns and camera images. In this work, we recognize t…
MultiXNet: Multiclass Multistage Multimodal Motion Prediction
Nemanja Djuric, Henggang Cui, Zhaoen Su +13
One of the critical pieces of the self-driving puzzle is understanding the surroundings of a self-driving vehicle (SDV) and predicting how these surroundings will change in the nea…
Improving Movement Predictions of Traffic Actors in Bird's-Eye View Models using GANs and Differentiable Trajectory Rasterization
Eason Wang, Henggang Cui, Sai Yalamanchi +3
One of the most critical pieces of the self-driving puzzle is the task of predicting future movement of surrounding traffic actors, which allows the autonomous vehicle to safely an…
Long-term Prediction of Vehicle Behavior using Short-term Uncertainty-aware Trajectories and High-definition Maps
Sai Yalamanchi, Tzu-Kuo Huang, Galen Clark Haynes +1
Motion prediction of surrounding vehicles is one of the most important tasks handled by a self-driving vehicle, and represents a critical step in the autonomous system necessary to…
Deep Kinematic Models for Kinematically Feasible Vehicle Trajectory Predictions
Henggang Cui, Thi Nguyen, Fang-Chieh Chou +4
Self-driving vehicles (SDVs) hold great potential for improving traffic safety and are poised to positively affect the quality of life of millions of people. To unlock this potenti…
Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
Fang-Chieh Chou, Tsung-Han Lin, Henggang Cui +6
Following detection and tracking of traffic actors, prediction of their future motion is the next critical component of a self-driving vehicle (SDV) technology, allowing the SDV to…
Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks
Henggang Cui, Vladan Radosavljevic, Fang-Chieh Chou +5
Autonomous driving presents one of the largest problems that the robotics and artificial intelligence communities are facing at the moment, both in terms of difficulty and potentia…
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving
Nemanja Djuric, Vladan Radosavljevic, Henggang Cui +5
We address one of the crucial aspects necessary for safe and efficient operations of autonomous vehicles, namely predicting future state of traffic actors in the autonomous vehicle…
Proceedings of the 2017 AdKDD & TargetAd Workshop
Abraham Bagherjeiran, Nemanja Djuric, Mihajlo Grbovic +4
Proceedings of the 2017 AdKDD and TargetAd Workshop held in conjunction with the 23rd ACM SIGKDD Conference on Knowledge Discovery and Data Mining Halifax, Nova Scotia, Canada.
Travel the World: Analyzing and Predicting Booking Behavior using E-mail Travel Receipts
Nemanja Djuric, Mihajlo Grbovic, Vladan Radosavljevic +3
Tourism industry has grown tremendously in the previous several decades. Despite its global impact, there still remain a number of open questions related to better understanding of…
Scalable Semantic Matching of Queries to Ads in Sponsored Search Advertising
Mihajlo Grbovic, Nemanja Djuric, Vladan Radosavljevic +6
Sponsored search represents a major source of revenue for web search engines. This popular advertising model brings a unique possibility for advertisers to target users' immediate…
Non-linear Label Ranking for Large-scale Prediction of Long-Term User Interests
Nemanja Djuric, Mihajlo Grbovic, Vladan Radosavljevic +2
We consider the problem of personalization of online services from the viewpoint of ad targeting, where we seek to find the best ad categories to be shown to each user, resulting i…
Hierarchical Neural Language Models for Joint Representation of Streaming Documents and their Content
Nemanja Djuric, Hao Wu, Vladan Radosavljevic +2
We consider the problem of learning distributed representations for documents in data streams. The documents are represented as low-dimensional vectors and are jointly learned with…
Network-Efficient Distributed Word2vec Training System for Large Vocabularies
Erik Ordentlich, Lee Yang, Andy Feng +5
Word2vec is a popular family of algorithms for unsupervised training of dense vector representations of words on large text corpuses. The resulting vectors have been shown to captu…
Gender and Interest Targeting for Sponsored Post Advertising at Tumblr
Mihajlo Grbovic, Vladan Radosavljevic, Nemanja Djuric +2
As one of the leading platforms for creative content, Tumblr offers advertisers a unique way of creating brand identity. Advertisers can tell their story through images, animation,…
E-commerce in Your Inbox: Product Recommendations at Scale
Mihajlo Grbovic, Vladan Radosavljevic, Nemanja Djuric +4
In recent years online advertising has become increasingly ubiquitous and effective. Advertisements shown to visitors fund sites and apps that publish digital content, manage socia…
Portrait of an Online Shopper: Understanding and Predicting Consumer Behavior
Farshad Kooti, Kristina Lerman, Luca Maria Aiello +3
Consumer spending accounts for a large fraction of the US economic activity. Increasingly, consumer activity is moving to the web, where digital traces of shopping and purchases pr…