Dragomir Anguelov
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
69
Venues
10
Active years
1999–2025
Best venue rank
A*
Where they publish
Papers
69 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | CVPR | S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Model with Spatio-Temporal Visual Representation. | Yichen Xie, Runsheng Xu, Tong He, Jyh-Jing Hwang, Katie Luo, Jingwei Ji, Hubert Lin, Letian Chen, Yiren Lu, Zhaoqi Leng, Dragomir Anguelov, Mingxing Tan |
| 2025 | CVPR | SceneDiffuser++: City-Scale Traffic Simulation via a Generative World Model. | Shuhan Tan, John Lambert, Hong Jeon, Sakshum Kulshrestha, Yijing Bai, Jing Luo, Dragomir Anguelov, Mingxing Tan, Chiyu Max Jiang |
| 2025 | CVPR | SceneCrafter: Controllable Multi-View Driving Scene Editing. | Zehao Zhu, Yuliang Zou, Chiyu Max Jiang, Bo Sun, Vincent Casser, Xiukun Huang, Jiahao Wang, Zhenpei Yang, Ruiqi Gao, Leonidas J. Guibas, Mingxing Tan, Dragomir Anguelov |
| 2025 | IROS | Enhanced Motion Forecasting with Plug-and-Play Multimodal Large Language Models. | Katie Luo, Jingwei Ji, Tong He, Runsheng Xu, Yichen Xie, Dragomir Anguelov, Mingxing Tan |
| 2025 | IROS | Drive&Gen: Co-Evaluating End-to-End Driving and Video Generation Models. | Jiahao Wang, Zhenpei Yang, Yijing Bai, Yingwei Li, Yuliang Zou, Bo Sun, Abhijit Kundu, Jos Lezama, Luna Yue Huang, Zehao Zhu, Jyh-Jing Hwang, Dragomir Anguelov, Mingxing Tan, Chiyu Max Jiang |
| 2024 | CVPR | MoST: Multi-modality Scene Tokenization for Motion Prediction. | Norman Mu, Jingwei Ji, Zhenpei Yang, Nate Harada, Haotian Tang, Kan Chen, Charles R. Qi, Runzhou Ge, Kratarth Goel, Zoey Yang, Scott Ettinger, Rami Al-Rfou, Dragomir Anguelov, Yin Zhou |
| 2024 | ICRA | WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting. | Kan Chen, Runzhou Ge, Hang Qiu, Rami Ai-Rfou, Charles R. Qi, Xuanyu Zhou, Zoey Yang, Scott Ettinger, Pei Sun, Zhaoqi Leng, Mustafa Baniodeh, Ivan Bogun, Weiyue Wang, Mingxing Tan, Dragomir Anguelov |
| 2024 | ICRA | LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection. | Wei-Chih Hung, Vincent Casser, Henrik Kretzschmar, Jyh-Jing Hwang, Dragomir Anguelov |
| 2024 | ICRA | PVTransformer: Point-to-Voxel Transformer for Scalable 3D Object Detection. | Zhaoqi Leng, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan |
| 2023 | CVPR | NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priors. | Congyue Deng, Chiyu Max Jiang, Charles R. Qi, Xinchen Yan, Yin Zhou, Leonidas J. Guibas, Dragomir Anguelov |
| 2023 | CVPR | MotionDiffuser: Controllable Multi-Agent Motion Prediction Using Diffusion. | Chiyu Max Jiang, Andre Cornman, Cheolho Park, Benjamin Sapp, Yin Zhou, Dragomir Anguelov |
| 2023 | CVPR | MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences. | Yingwei Li, Charles R. Qi, Yin Zhou, Chenxi Liu, Dragomir Anguelov |
| 2023 | CVPR | GINA-3D: Learning to Generate Implicit Neural Assets in the Wild. | Bokui Shen, Xinchen Yan, Charles R. Qi, Mahyar Najibi, Boyang Deng, Leonidas J. Guibas, Yin Zhou, Dragomir Anguelov |
| 2023 | CVPR | 3D Human Keypoints Estimation from Point Clouds in the Wild without Human Labels. | Zhenzhen Weng, Alexander S. Gorban, Jingwei Ji, Mahyar Najibi, Yin Zhou, Dragomir Anguelov |
| 2023 | ICCV | Unsupervised 3D Perception with 2D Vision-Language Distillation for Autonomous Driving. | Mahyar Najibi, Jingwei Ji, Yin Zhou, Charles R. Qi, Xinchen Yan, Scott Ettinger, Dragomir Anguelov |
| 2023 | ICRA | Lidar Augment: Searching for Scalable 3D LiDAR Data Augmentations. | Zhaoqi Leng, Guowang Li, Chenxi Liu, Ekin Dogus Cubuk, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan |
| 2023 | IROS | LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection. | Tong He, Pei Sun, Zhaoqi Leng, Chenxi Liu, Dragomir Anguelov, Mingxing Tan |
| 2023 | IROS | Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. | Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, Sergey Levine |
| 2022 | CoRL | JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving. | Wenjie Luo, Cheol Park, Andre Cornman, Benjamin Sapp, Dragomir Anguelov |
| 2022 | CoRL | HUM3DIL: Semi-supervised Multi-modal 3D HumanPose Estimation for Autonomous Driving. | Andrei Zanfir, Mihai Zanfir, Alexander N. Gorban, Jingwei Ji, Yin Zhou, Dragomir Anguelov, Cristian Sminchisescu |
| 2022 | CVPR | Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving. | Jingxiao Zheng, Xinwei Shi, Alexander N. Gorban, Junhua Mao, Yang Song, Charles R. Qi, Ting Liu, Visesh Chari, Andre Cornman, Yin Zhou, Congcong Li, Dragomir Anguelov |
| 2022 | CVPR | RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding. | Xuanyu Zhou, Charles R. Qi, Yin Zhou, Dragomir Anguelov |
| 2022 | ECCV | CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection. | Jyh-Jing Hwang, Henrik Kretzschmar, Joshua Manela, Sean Rafferty, Nicholas Armstrong-Crews, Tiffany L. Chen, Dragomir Anguelov |
| 2022 | ECCV | Improving the Intra-class Long-Tail in 3D Detection via Rare Example Mining. | Chiyu Max Jiang, Mahyar Najibi, Charles R. Qi, Yin Zhou, Dragomir Anguelov |
| 2022 | ECCV | PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. | Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov |
| 2022 | ECCV | LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds. | Chenxi Liu, Zhaoqi Leng, Pei Sun, Shuyang Cheng, Charles R. Qi, Yin Zhou, Mingxing Tan, Dragomir Anguelov |
| 2022 | ECCV | LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds. | Minghua Liu, Yin Zhou, Charles R. Qi, Boqing Gong, Hao Su, Dragomir Anguelov |
| 2022 | ECCV | Motion Inspired Unsupervised Perception and Prediction in Autonomous Driving. | Mahyar Najibi, Jingwei Ji, Yin Zhou, Charles R. Qi, Xinchen Yan, Scott Ettinger, Dragomir Anguelov |
| 2022 | ECCV | SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds. | Pei Sun, Mingxing Tan, Weiyue Wang, Chenxi Liu, Fei Xia, Zhaoqi Leng, Dragomir Anguelov |
| 2022 | ICLR | PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. | Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Jay Shi, Shuyang Cheng, Dragomir Anguelov |
| 2022 | ICRA | Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation. | Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin, Punit Shah, Kyriacos Shiarlis, Dragomir Anguelov, Mark Palatucci, Brandyn White, Shimon Whiteson |
| 2022 | ICRA | Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking. | Longlong Jing, Ruichi Yu, Henrik Kretzschmar, Kang Li, Charles R. Qi, Hang Zhao, Alper Ayvaci, Xu Chen, Dillon Cower, Yingwei Li, Yurong You, Han Deng, Congcong Li, Dragomir Anguelov |
| 2022 | ICRA | StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving. | Jinkyu Kim, Reza Mahjourian, Scott Ettinger, Mayank Bansal, Brandyn White, Ben Sapp, Dragomir Anguelov |
| 2022 | IROS | Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. | Eli Bronstein, Mark Palatucci, Dominik Notz, Brandyn White, Alex Kuefler, Yiren Lu, Supratik Paul, Payam Nikdel, Paul Mougin, Hongge Chen, Justin Fu, Austin Abrams, Punit Shah, Evan Racah, Benjamin Frenkel, Shimon Whiteson, Dragomir Anguelov |
| 2022 | ICRA | MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction. | Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava, Khaled S. Refaat, Nigamaa Nayakanti, Andre Cornman, Kan Chen, Bertrand Douillard, Chi-Pang Lam, Dragomir Anguelov, Benjamin Sapp |
| 2022 | ICRA | Multi-Class 3D Object Detection with Single-Class Supervision. | Mao Ye, Chenxi Liu, Maoqing Yao, Weiyue Wang, Zhaoqi Leng, Charles R. Qi, Dragomir Anguelov |
| 2021 | CVPR | To the Point: Efficient 3D Object Detection in the Range Image With Graph Convolution Kernels. | Yuning Chai, Pei Sun, Jiquan Ngiam, Weiyue Wang, Benjamin Caine, Vijay Vasudevan, Xiao Zhang, Dragomir Anguelov |
| 2021 | CVPR | HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps. | Lu Mi, Hang Zhao, Charlie Nash, Xiaohan Jin, Jiyang Gao, Chen Sun, Cordelia Schmid, Nir Shavit, Yuning Chai, Dragomir Anguelov |
| 2021 | CVPR | Offboard 3D Object Detection From Point Cloud Sequences. | Charles R. Qi, Yin Zhou, Mahyar Najibi, Pei Sun, Khoa Vo, Boyang Deng, Dragomir Anguelov |
| 2021 | CVPR | RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection. | Pei Sun, Weiyue Wang, Yuning Chai, Gamaleldin Elsayed, Alex Bewley, Xiao Zhang, Cristian Sminchisescu, Dragomir Anguelov |
| 2021 | ICCV | Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset. | Scott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu, Hang Zhao, Sabeek Pradhan, Yuning Chai, Ben Sapp, Charles R. Qi, Yin Zhou, Zoey Yang, Aurelien Chouard, Pei Sun, Jiquan Ngiam, Vijay Vasudevan, Alexander McCauley, Jonathon Shlens, Dragomir Anguelov |
| 2021 | ICCV | SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation. | Qiangeng Xu, Yin Zhou, Weiyue Wang, Charles R. Qi, Dragomir Anguelov |
| 2021 | ICRA | Identifying Driver Interactions via Conditional Behavior Prediction. | Ekaterina I. Tolstaya, Reza Mahjourian, Carlton Downey, Balakrishnan Varadarajan, Benjamin Sapp, Dragomir Anguelov |
| 2020 | CoRL | Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection. | Alex Bewley, Pei Sun, Thomas Mensink, Dragomir Anguelov, Cristian Sminchisescu |
| 2020 | CoRL | TNT: Target-driven Trajectory Prediction. | Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, Congcong Li, Dragomir Anguelov |
| 2020 | CVPR | VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation. | Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Congcong Li, Cordelia Schmid |
| 2020 | CVPR | Scalability in Perception for Autonomous Driving: Waymo Open Dataset. | Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, Dragomir Anguelov |
| 2020 | CVPR | SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving. | Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, Henrik Kretzschmar |
| 2020 | CVPR | STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction. | Zhishuai Zhang, Jiyang Gao, Junhua Mao, Yukai Liu, Dragomir Anguelov, Congcong Li |
| 2020 | ECCV | Improving 3D Object Detection Through Progressive Population Based Augmentation. | Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov |
| 2019 | CoRL | MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction. | Yuning Chai, Benjamin Sapp, Mayank Bansal, Dragomir Anguelov |
| 2019 | CoRL | End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds. | Yin Zhou, Pei Sun, Yu Zhang, Dragomir Anguelov, Jiyang Gao, Tom Ouyang, James Guo, Jiquan Ngiam, Vijay Vasudevan |
| 2018 | CVPR | PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation. | Danfei Xu, Dragomir Anguelov, Ashesh Jain |
| 2017 | CVPR | 3D Bounding Box Estimation Using Deep Learning and Geometry. | Arsalan Mousavian, Dragomir Anguelov, John Flynn, Jana Kosecka |
| 2016 | ECCV | SSD: Single Shot MultiBox Detector. | Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, Alexander C. Berg |
| 2016 | WACV | Self-taught object localization with deep networks. | Loris Bazzani, Alessandro Bergamo, Dragomir Anguelov, Lorenzo Torresani |
| 2015 | CVPR | Going deeper with convolutions. | Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich |
| 2014 | CVPR | Scalable Object Detection Using Deep Neural Networks. | Dumitru Erhan, Christian Szegedy, Alexander Toshev, Dragomir Anguelov |
| 2014 | CVPR | Capturing Long-Tail Distributions of Object Subcategories. | Xiangxin Zhu, Dragomir Anguelov, Deva Ramanan |
| 2010 | ICRA | High quality pose estimation by aligning multiple scans to a latent map. | Qi-Xing Huang, Dragomir Anguelov |
| 2010 | IROS | Hybrid hessians for flexible optimization of pose graphs. | Matthew Koichi Grimes, Dragomir Anguelov, Yann LeCun |
| 2007 | CVPR | Contextual Identity Recognition in Personal Photo Albums. | Dragomir Anguelov, Kuang-chih Lee, Salih Burak Gktrk, Baris Sumengen |
| 2006 | CVPR | Object Pose Detection in Range Scan Data. | Jim Rodgers, Dragomir Anguelov, Hoi-Cheung Pang, Daphne Koller |
| 2005 | CVPR | Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data. | Dragomir Anguelov, Benjamin Taskar, Vassil Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz, Andrew Y. Ng |
| 2004 | ICRA | Detecting and Modeling Doors with Mobile Robots. | Dragomir Anguelov, Daphne Koller, Evan Parker, Sebastian Thrun |
| 2004 | UAI | Recovering Articulated Object Models from 3D Range Data. | Dragomir Anguelov, Daphne Koller, Hoi-Cheung Pang, Praveen Srinivasan, Sebastian Thrun |
| 2002 | UAI | Learning Hierarchical Object Maps of Non-Stationary Environments with Mobile Robots. | Dragomir Anguelov, Rahul Biswas, Daphne Koller, Benson Limketkai, Sebastian Thrun |
| 2000 | KDD | Mining the stock market (extended abstract): which measure is best? | Martin Gavrilov, Dragomir Anguelov, Piotr Indyk, Rajeev Motwani |
| 1999 | UAI | A General Algorithm for Approximate Inference and Its Application to Hybrid Bayes Nets. | Daphne Koller, Uri Lerner, Dragomir Anguelov |