Dragomir Anguelov

Affiliations:

Stanford University, USA

According to our database¹, Dragomir Anguelov authored at least 82 papers between 1999 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2023

WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting.

[BibT_eX]

[DOI]

CoRR, 2023

The Waymo Open Sim Agents Challenge.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios.

[BibT_eX]

[DOI]

IROS, 2023

LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection.

[BibT_eX]

[DOI]

IROS, 2023

Lidar Augment: Searching for Scalable 3D LiDAR Data Augmentations.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Unsupervised 3D Perception with 2D Vision-Language Distillation for Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

3D Human Keypoints Estimation from Point Clouds in the Wild without Human Labels.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

GINA-3D: Learning to Generate Implicit Neural Assets in the Wild.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

MotionDiffuser: Controllable Multi-Agent Motion Prediction Using Diffusion.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priors.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Occupancy Flow Fields for Motion Forecasting in Autonomous Driving.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2022

JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving.

[BibT_eX]

[DOI]

CoRR, 2022

HUM3DIL: Semi-supervised Multi-modal 3D Human Pose Estimation for Autonomous Driving.

[BibT_eX]

[DOI]

Cristian Sminchisescu

CoRR, 2022

LidarAugment: Searching for Scalable 3D LiDAR Data Augmentations.

[BibT_eX]

[DOI]

CoRR, 2022

LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection.

[BibT_eX]

[DOI]

CoRR, 2022

Waymo Open Dataset: Panoramic Video Panoptic Segmentation.

[BibT_eX]

[DOI]

CoRR, 2022

PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions.

[BibT_eX]

[DOI]

CoRR, 2022

GradTail: Learning Long-Tailed Data Using Gradient-based Sample Weighting.

[BibT_eX]

[DOI]

CoRR, 2022

Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Multi-Class 3D Object Detection with Single-Class Supervision.

[BibT_eX]

[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction.

[BibT_eX]

[DOI]

Balakrishnan Varadarajan

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking.

[BibT_eX]

[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation.

[BibT_eX]

[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

Motion Inspired Unsupervised Perception and Prediction in Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

Improving the Intra-class Long-Tail in 3D Detection via Rare Example Mining.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection.

[BibT_eX]

[DOI]

Nicholas Armstrong-Crews

Tiffany Chen

Dragomir Anguelov

Proceedings of the Computer Vision - ECCV 2022, 2022

RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

HUM3DIL: Semi-supervised Multi-modal 3D HumanPose Estimation for Autonomous Driving.

[BibT_eX]

[DOI]

Cristian Sminchisescu

Proceedings of the Conference on Robot Learning, 2022

JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2022

2021

Revisiting 3D Object Detection From an Egocentric Perspective.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Identifying Driver Interactions via Conditional Behavior Prediction.

[BibT_eX]

[DOI]

Ekaterina I. Tolstaya

Reza Mahjourian

Carlton Downey

Balakrishnan Varadarajan

Benjamin Sapp

Dragomir Anguelov

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection.

[BibT_eX]

[DOI]

Cristian Sminchisescu

Dragomir Anguelov

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Offboard 3D Object Detection From Point Cloud Sequences.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

To the Point: Efficient 3D Object Detection in the Range Image With Graph Convolution Kernels.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

SoDA: Multi-Object Tracking with Soft Data Association.

[BibT_eX]

[DOI]

CoRR, 2020

Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Improving 3D Object Detection Through Progressive Population Based Augmentation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Scalability in Perception for Autonomous Driving: Waymo Open Dataset.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

TNT: Target-driven Trajectory Prediction.

[BibT_eX]

[DOI]

Balakrishnan Varadarajan

Proceedings of the 4th Conference on Robot Learning, 2020

Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection.

[BibT_eX]

[DOI]

Cristian Sminchisescu

Proceedings of the 4th Conference on Robot Learning, 2020

2019

End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds.

[BibT_eX]

[DOI]

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction.

[BibT_eX]

[DOI]

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018

PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation.

[BibT_eX]

[DOI]

Danfei Xu

Dragomir Anguelov

Ashesh Jain

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

3D Bounding Box Estimation Using Deep Learning and Geometry.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Self-taught object localization with deep networks.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, 2016

SSD: Single Shot MultiBox Detector.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2016, 2016

2015

Self-informed neural network structure learning.

[BibT_eX]

[DOI]

David Warde-Farley

Andrew Rabinovich

Dragomir Anguelov

Proceedings of the 3rd International Conference on Learning Representations, 2015

Training Deep Neural Networks on Noisy Labels with Bootstrapping.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Conference on Learning Representations, 2015

Going deeper with convolutions.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

Scalable, High-Quality Object Detection.

[BibT_eX]

[DOI]

CoRR, 2014

Capturing Long-Tail Distributions of Object Subcategories.

[BibT_eX]

[DOI]

Xiangxin Zhu

Dragomir Anguelov

Deva Ramanan

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Scalable Object Detection Using Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2010

Google Street View: Capturing the World at Street Level.

[BibT_eX]

[DOI]

Computer, 2010

Hybrid hessians for flexible optimization of pose graphs.

[BibT_eX]

[DOI]

Matthew Koichi Grimes

Dragomir Anguelov

Yann LeCun

Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

High quality pose estimation by aligning multiple scans to a latent map.

[BibT_eX]

[DOI]

Qi-Xing Huang

Dragomir Anguelov

Proceedings of the IEEE International Conference on Robotics and Automation, 2010

2008

Markov random field models for hair and face segmentation.

[BibT_eX]

[DOI]

Proceedings of the 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008), 2008

2007

Contextual Identity Recognition in Personal Photo Albums.

[BibT_eX]

[DOI]

Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007

2006

Learning models of shape from 3D range data.

[BibT_eX]

[DOI]

Dragomir Anguelov

PhD thesis, 2006

Object Pose Detection in Range Scan Data.

[BibT_eX]

[DOI]

Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006

2005

SCAPE: shape completion and animation of people.

[BibT_eX]

[DOI]

ACM Trans. Graph., 2005

Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data.

[BibT_eX]

[DOI]

Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

2004

Recovering Articulated Object Models from 3D Range Data.

[BibT_eX]

[DOI]

Proceedings of the UAI '04, 2004

The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Detecting and Modeling Doors with Mobile Robots.

[BibT_eX]

[DOI]

Proceedings of the 2004 IEEE International Conference on Robotics and Automation, 2004

2002

Learning Hierarchical Object Maps of Non-Stationary Environments with Mobile Robots.

[BibT_eX]

[DOI]

Proceedings of the UAI '02, 2002

2000

Mining the stock market (extended abstract): which measure is best?

[BibT_eX]

[DOI]

Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000

1999

A General Algorithm for Approximate Inference and Its Application to Hybrid Bayes Nets.

[BibT_eX]

[DOI]

Daphne Koller

Uri Lerner

Dragomir Anguelov

Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Dragomir Anguelov

Timeline

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