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Dragomir Anguelov
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- affiliation: Stanford University, USA
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2020 – today
- 2024
- [i65]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:
MoST: Multi-modality Scene Tokenization for Motion Prediction. CoRR abs/2404.19531 (2024) - [i64]Zhaoqi Leng, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan:
PVTransformer: Point-to-Voxel Transformer for Scalable 3D Object Detection. CoRR abs/2405.02811 (2024) - 2023
- [c68]Zhenzhen Weng, Alexander S. Gorban, Jingwei Ji, Mahyar Najibi, Yin Zhou, Dragomir Anguelov:
3D Human Keypoints Estimation from Point Clouds in the Wild without Human Labels. CVPR 2023: 1158-1167 - [c67]Bokui Shen, Xinchen Yan, Charles R. Qi, Mahyar Najibi, Boyang Deng, Leonidas J. Guibas, Yin Zhou, Dragomir Anguelov:
GINA-3D: Learning to Generate Implicit Neural Assets in the Wild. CVPR 2023: 4913-4926 - [c66]Yingwei Li, Charles R. Qi, Yin Zhou, Chenxi Liu, Dragomir Anguelov:
MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences. CVPR 2023: 9329-9339 - [c65]Chiyu Max Jiang, Andre Cornman, Cheolho Park, Benjamin Sapp, Yin Zhou, Dragomir Anguelov:
MotionDiffuser: Controllable Multi-Agent Motion Prediction Using Diffusion. CVPR 2023: 9644-9653 - [c64]Congyue Deng, Chiyu Max Jiang, Charles R. Qi, Xinchen Yan, Yin Zhou, Leonidas J. Guibas, Dragomir Anguelov:
NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priors. CVPR 2023: 20637-20647 - [c63]Mahyar Najibi, Jingwei Ji, Yin Zhou, Charles R. Qi, Xinchen Yan, Scott Ettinger, Dragomir Anguelov:
Unsupervised 3D Perception with 2D Vision-Language Distillation for Autonomous Driving. ICCV 2023: 8568-8578 - [c62]Zhaoqi Leng, Guowang Li, Chenxi Liu, Ekin Dogus Cubuk, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan:
Lidar Augment: Searching for Scalable 3D LiDAR Data Augmentations. ICRA 2023: 7039-7045 - [c61]Tong He, Pei Sun, Zhaoqi Leng, Chenxi Liu, Dragomir Anguelov, Mingxing Tan:
LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection. IROS 2023: 1637-1644 - [c60]Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust
, Shimon Whiteson, Dragomir Anguelov, Sergey Levine:
Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. IROS 2023: 7553-7560 - [c59]Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John D. Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Yang, Brandyn White, Aleksandra Faust, Rowan McAllister, Dragomir Anguelov, Benjamin Sapp:
Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research. NeurIPS 2023 - [c58]Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nicholas Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Yang, Shimon Whiteson, Brandyn White, Dragomir Anguelov:
The Waymo Open Sim Agents Challenge. NeurIPS 2023 - [i63]Bokui Shen, Xinchen Yan, Charles R. Qi, Mahyar Najibi, Boyang Deng, Leonidas J. Guibas, Yin Zhou, Dragomir Anguelov:
GINA-3D: Learning to Generate Implicit Neural Assets in the Wild. CoRR abs/2304.02163 (2023) - [i62]Kan Chen, Runzhou Ge, Hang Qiu, Rami Ai-Rfou, Charles R. Qi, Xuanyu Zhou, Zoey Yang, Scott Ettinger, Pei Sun, Zhaoqi Leng, Mustafa Mustafa, Ivan Bogun, Weiyue Wang, Mingxing Tan, Dragomir Anguelov:
WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting. CoRR abs/2304.03834 (2023) - [i61]Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nick Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Yang, Shimon Whiteson, Brandyn White, Dragomir Anguelov:
The Waymo Open Sim Agents Challenge. CoRR abs/2305.12032 (2023) - [i60]Chiyu Max Jiang, Andre Cornman, Cheolho Park, Ben Sapp, Yin Zhou, Dragomir Anguelov:
MotionDiffuser: Controllable Multi-Agent Motion Prediction using Diffusion. CoRR abs/2306.03083 (2023) - [i59]Yingwei Li, Charles R. Qi, Yin Zhou, Chenxi Liu, Dragomir Anguelov:
MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences. CoRR abs/2306.03206 (2023) - [i58]Zhenzhen Weng, Alexander S. Gorban, Jingwei Ji, Mahyar Najibi, Yin Zhou, Dragomir Anguelov:
3D Human Keypoints Estimation From Point Clouds in the Wild Without Human Labels. CoRR abs/2306.04745 (2023) - [i57]Mahyar Najibi, Jingwei Ji, Yin Zhou, Charles R. Qi, Xinchen Yan, Scott Ettinger, Dragomir Anguelov:
Unsupervised 3D Perception with 2D Vision-Language Distillation for Autonomous Driving. CoRR abs/2309.14491 (2023) - [i56]Tong He, Pei Sun, Zhaoqi Leng, Chenxi Liu, Dragomir Anguelov, Mingxing Tan:
LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection. CoRR abs/2309.16870 (2023) - [i55]Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John D. Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Yang, Brandyn White, Aleksandra Faust
, Rowan McAllister, Dragomir Anguelov, Benjamin Sapp:
Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research. CoRR abs/2310.08710 (2023) - 2022
- [j3]Reza Mahjourian
, Jinkyu Kim
, Yuning Chai, Mingxing Tan, Ben Sapp, Dragomir Anguelov:
Occupancy Flow Fields for Motion Forecasting in Autonomous Driving. IEEE Robotics Autom. Lett. 7(2): 5639-5646 (2022) - [c57]Andrei Zanfir, Mihai Zanfir, Alexander N. Gorban, Jingwei Ji, Yin Zhou, Dragomir Anguelov, Cristian Sminchisescu:
HUM3DIL: Semi-supervised Multi-modal 3D HumanPose Estimation for Autonomous Driving. CoRL 2022: 1114-1124 - [c56]Wenjie Luo, Cheol Park, Andre Cornman, Benjamin Sapp, Dragomir Anguelov:
JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving. CoRL 2022: 1457-1467 - [c55]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:
Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving. CVPR Workshops 2022: 4477-4486 - [c54]Xuanyu Zhou, Charles R. Qi, Yin Zhou, Dragomir Anguelov:
RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding. CVPR 2022: 17191-17200 - [c53]Minghua Liu, Yin Zhou, Charles R. Qi, Boqing Gong, Hao Su, Dragomir Anguelov:
LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds. ECCV (39) 2022: 70-89 - [c52]Chiyu Max Jiang, Mahyar Najibi, Charles R. Qi, Yin Zhou, Dragomir Anguelov:
Improving the Intra-class Long-Tail in 3D Detection via Rare Example Mining. ECCV (10) 2022: 158-175 - [c51]Chenxi Liu, Zhaoqi Leng, Pei Sun, Shuyang Cheng, Charles R. Qi, Yin Zhou, Mingxing Tan, Dragomir Anguelov:
LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds. ECCV (21) 2022: 158-175 - [c50]Jyh-Jing Hwang, Henrik Kretzschmar, Joshua Manela, Sean Rafferty, Nicholas Armstrong-Crews, Tiffany Chen, Dragomir Anguelov:
CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection. ECCV (38) 2022: 388-405 - [c49]Mahyar Najibi, Jingwei Ji, Yin Zhou, Charles R. Qi, Xinchen Yan, Scott Ettinger, Dragomir Anguelov:
Motion Inspired Unsupervised Perception and Prediction in Autonomous Driving. ECCV (38) 2022: 424-443 - [c48]Pei Sun, Mingxing Tan, Weiyue Wang, Chenxi Liu, Fei Xia, Zhaoqi Leng, Dragomir Anguelov:
SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds. ECCV (10) 2022: 426-442 - [c47]Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov:
PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. ECCV (31) 2022: 555-572 - [c46]Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Jay Shi, Shuyang Cheng, Dragomir Anguelov:
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. ICLR 2022 - [c45]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:
Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking. ICRA 2022: 366-373 - [c44]Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin, Punit Shah, Kyriacos Shiarlis, Dragomir Anguelov, Mark Palatucci, Brandyn White, Shimon Whiteson:
Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation. ICRA 2022: 2445-2451 - [c43]Mao Ye, Chenxi Liu, Maoqing Yao, Weiyue Wang, Zhaoqi Leng, Charles R. Qi, Dragomir Anguelov:
Multi-Class 3D Object Detection with Single-Class Supervision. ICRA 2022: 5123-5130 - [c42]Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava, Khaled S. Refaat, Nigamaa Nayakanti, Andre Cornman, Kan Chen, Bertrand Douillard, Chi-Pang Lam, Dragomir Anguelov, Benjamin Sapp:
MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction. ICRA 2022: 7814-7821 - [c41]Jinkyu Kim, Reza Mahjourian, Scott Ettinger, Mayank Bansal, Brandyn White, Ben Sapp, Dragomir Anguelov:
StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving. ICRA 2022: 8957-8963 - [c40]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:
Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. IROS 2022: 8652-8659 - [i54]Zhao Chen, Vincent Casser, Henrik Kretzschmar, Dragomir Anguelov:
GradTail: Learning Long-Tailed Data Using Gradient-based Sample Weighting. CoRR abs/2201.05938 (2022) - [i53]Reza Mahjourian, Jinkyu Kim, Yuning Chai, Mingxing Tan, Benjamin Sapp, Dragomir Anguelov:
Occupancy Flow Fields for Motion Forecasting in Autonomous Driving. CoRR abs/2203.03875 (2022) - [i52]Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Xiaojie Shi, Shuyang Cheng, Dragomir Anguelov:
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. CoRR abs/2204.12511 (2022) - [i51]Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin, Punit Shah, Kyriacos Shiarlis, Dragomir Anguelov, Mark Palatucci, Brandyn White, Shimon Whiteson:
Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation. CoRR abs/2205.03195 (2022) - [i50]Mao Ye, Chenxi Liu, Maoqing Yao, Weiyue Wang, Zhaoqi Leng, Charles R. Qi, Dragomir Anguelov:
Multi-Class 3D Object Detection with Single-Class Supervision. CoRR abs/2205.05703 (2022) - [i49]Jinkyu Kim, Reza Mahjourian, Scott Ettinger, Mayank Bansal, Brandyn White, Ben Sapp, Dragomir Anguelov:
StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving. CoRR abs/2206.00991 (2022) - [i48]Xuanyu Zhou, Charles R. Qi, Yin Zhou, Dragomir Anguelov:
RIDDLE: Lidar Data Compression with Range Image Deep Delta Encoding. CoRR abs/2206.01738 (2022) - [i47]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:
Depth Estimation Matters Most: Improving Per-Object Depth Estimation for Monocular 3D Detection and Tracking. CoRR abs/2206.03666 (2022) - [i46]Jieru Mei, Alex Zihao Zhu, Xinchen Yan, Hang Yan, Siyuan Qiao, Yukun Zhu, Liang-Chieh Chen, Henrik Kretzschmar, Dragomir Anguelov:
Waymo Open Dataset: Panoramic Video Panoptic Segmentation. CoRR abs/2206.07704 (2022) - [i45]Wei-Chih Hung, Henrik Kretzschmar, Vincent Casser, Jyh-Jing Hwang, Dragomir Anguelov:
LET-3D-AP: Longitudinal Error Tolerant 3D Average Precision for Camera-Only 3D Detection. CoRR abs/2206.07705 (2022) - [i44]Chenxi Liu, Zhaoqi Leng, Pei Sun, Shuyang Cheng, Charles R. Qi, Yin Zhou, Mingxing Tan, Dragomir Anguelov:
LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds. CoRR abs/2210.05018 (2022) - [i43]Pei Sun, Mingxing Tan, Weiyue Wang, Chenxi Liu, Fei Xia, Zhaoqi Leng, Dragomir Anguelov:
SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds. CoRR abs/2210.07372 (2022) - [i42]Mahyar Najibi, Jingwei Ji, Yin Zhou, Charles R. Qi, Xinchen Yan, Scott Ettinger, Dragomir Anguelov:
Motion Inspired Unsupervised Perception and Prediction in Autonomous Driving. CoRR abs/2210.08061 (2022) - [i41]Minghua Liu, Yin Zhou, Charles R. Qi, Boqing Gong, Hao Su, Dragomir Anguelov:
LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds. CoRR abs/2210.08064 (2022) - [i40]Chiyu Max Jiang, Mahyar Najibi, Charles R. Qi, Yin Zhou, Dragomir Anguelov:
Improving the Intra-class Long-tail in 3D Detection via Rare Example Mining. CoRR abs/2210.08375 (2022) - [i39]Jyh-Jing Hwang, Henrik Kretzschmar, Joshua Manela, Sean Rafferty, Nicholas Armstrong-Crews, Tiffany Chen, Dragomir Anguelov:
CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection. CoRR abs/2210.09267 (2022) - [i38]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:
Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. CoRR abs/2210.09539 (2022) - [i37]Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov:
PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. CoRR abs/2210.13428 (2022) - [i36]Zhaoqi Leng, Guowang Li, Chenxi Liu, Ekin Dogus Cubuk, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan:
LidarAugment: Searching for Scalable 3D LiDAR Data Augmentations. CoRR abs/2210.13488 (2022) - [i35]Congyue Deng, Chiyu Max Jiang, Charles R. Qi, Xinchen Yan, Yin Zhou, Leonidas J. Guibas, Dragomir Anguelov:
NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priors. CoRR abs/2212.03267 (2022) - [i34]Andrei Zanfir, Mihai Zanfir, Alexander N. Gorban, Jingwei Ji, Yin Zhou, Dragomir Anguelov, Cristian Sminchisescu:
HUM3DIL: Semi-supervised Multi-modal 3D Human Pose Estimation for Autonomous Driving. CoRR abs/2212.07729 (2022) - [i33]Wenjie Luo, Cheolho Park, Andre Cornman, Benjamin Sapp, Dragomir Anguelov:
JFP: Joint Future Prediction with Interactive Multi-Agent Modeling for Autonomous Driving. CoRR abs/2212.08710 (2022) - [i32]Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Becca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust
, Shimon Whiteson, Dragomir Anguelov, Sergey Levine:
Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios. CoRR abs/2212.11419 (2022) - 2021
- [c39]Lu Mi, Hang Zhao, Charlie Nash, Xiaohan Jin, Jiyang Gao, Chen Sun, Cordelia Schmid, Nir Shavit, Yuning Chai, Dragomir Anguelov:
HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps. CVPR 2021: 4227-4236 - [c38]Pei Sun, Weiyue Wang, Yuning Chai, Gamaleldin Elsayed, Alex Bewley, Xiao Zhang, Cristian Sminchisescu, Dragomir Anguelov:
RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection. CVPR 2021: 5725-5734 - [c37]Charles R. Qi, Yin Zhou, Mahyar Najibi, Pei Sun, Khoa Vo, Boyang Deng, Dragomir Anguelov:
Offboard 3D Object Detection From Point Cloud Sequences. CVPR 2021: 6134-6144 - [c36]Yuning Chai, Pei Sun, Jiquan Ngiam, Weiyue Wang, Benjamin Caine, Vijay Vasudevan, Xiao Zhang, Dragomir Anguelov:
To the Point: Efficient 3D Object Detection in the Range Image With Graph Convolution Kernels. CVPR 2021: 16000-16009 - [c35]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:
Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset. ICCV 2021: 9690-9699 - [c34]Qiangeng Xu, Yin Zhou, Weiyue Wang, Charles R. Qi, Dragomir Anguelov:
SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation. ICCV 2021: 15426-15436 - [c33]Ekaterina I. Tolstaya, Reza Mahjourian, Carlton Downey, Balakrishnan Varadarajan, Benjamin Sapp, Dragomir Anguelov:
Identifying Driver Interactions via Conditional Behavior Prediction. ICRA 2021: 3473-3479 - [c32]Boyang Deng, Charles R. Qi, Mahyar Najibi, Thomas A. Funkhouser, Yin Zhou, Dragomir Anguelov:
Revisiting 3D Object Detection From an Egocentric Perspective. NeurIPS 2021: 26066-26079 - [i31]Charles R. Qi, Yin Zhou, Mahyar Najibi, Pei Sun, Khoa Vo, Boyang Deng, Dragomir Anguelov:
Offboard 3D Object Detection from Point Cloud Sequences. CoRR abs/2103.05073 (2021) - [i30]Ekaterina I. Tolstaya, Reza Mahjourian, Carlton Downey, Balakrishnan Varadarajan, Benjamin Sapp, Dragomir Anguelov:
Identifying Driver Interactions via Conditional Behavior Prediction. CoRR abs/2104.09959 (2021) - [i29]Scott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu, Hang Zhao, Sabeek Pradhan, Yuning Chai, Benjamin Sapp, Charles R. Qi, Yin Zhou, Zoey Yang, Aurelien Chouard, Pei Sun, Jiquan Ngiam, Vijay Vasudevan, Alexander McCauley, Jonathon Shlens, Dragomir Anguelov:
Large Scale Interactive Motion Forecasting for Autonomous Driving : The Waymo Open Motion Dataset. CoRR abs/2104.10133 (2021) - [i28]Pei Sun, Weiyue Wang, Yuning Chai, Gamaleldin Elsayed, Alex Bewley, Xiao Zhang, Cristian Sminchisescu, Dragomir Anguelov:
RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection. CoRR abs/2106.13365 (2021) - [i27]Yuning Chai, Pei Sun, Jiquan Ngiam, Weiyue Wang, Benjamin Caine, Vijay Vasudevan, Xiao Zhang, Dragomir Anguelov:
To the Point: Efficient 3D Object Detection in the Range Image with Graph Convolution Kernels. CoRR abs/2106.13381 (2021) - [i26]Lu Mi, Hang Zhao, Charlie Nash, Xiaohan Jin, Jiyang Gao, Chen Sun, Cordelia Schmid, Nir Shavit, Yuning Chai, Dragomir Anguelov:
HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps. CoRR abs/2106.14880 (2021) - [i25]Qiangeng Xu, Yin Zhou, Weiyue Wang, Charles R. Qi, Dragomir Anguelov:
SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation. CoRR abs/2108.06709 (2021) - [i24]Balakrishnan Varadarajan, Ahmed Hefny, Avikalp Srivastava, Khaled S. Refaat, Nigamaa Nayakanti, Andre Cornman, Kan Chen, Bertrand Douillard, Chi-Pang Lam, Dragomir Anguelov, Benjamin Sapp:
MultiPath++: Efficient Information Fusion and Trajectory Aggregation for Behavior Prediction. CoRR abs/2111.14973 (2021) - [i23]Boyang Deng, Charles R. Qi, Mahyar Najibi, Thomas A. Funkhouser, Yin Zhou, Dragomir Anguelov:
Revisiting 3D Object Detection From an Egocentric Perspective. CoRR abs/2112.07787 (2021) - [i22]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:
Multi-modal 3D Human Pose Estimation with 2D Weak Supervision in Autonomous Driving. CoRR abs/2112.12141 (2021) - 2020
- [c31]Alex Bewley, Pei Sun, Thomas Mensink, Dragomir Anguelov, Cristian Sminchisescu:
Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection. CoRL 2020: 627-641 - [c30]Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, Congcong Li, Dragomir Anguelov:
TNT: Target-driven Trajectory Prediction. CoRL 2020: 895-904 - [c29]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:
Scalability in Perception for Autonomous Driving: Waymo Open Dataset. CVPR 2020: 2443-2451 - [c28]Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, Henrik Kretzschmar:
SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving. CVPR 2020: 11115-11124 - [c27]Zhishuai Zhang, Jiyang Gao, Junhua Mao, Yukai Liu, Dragomir Anguelov, Congcong Li:
STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction. CVPR 2020: 11343-11352 - [c26]Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Congcong Li, Cordelia Schmid:
VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation. CVPR 2020: 11522-11530 - [c25]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:
Improving 3D Object Detection Through Progressive Population Based Augmentation. ECCV (21) 2020: 279-294 - [c24]Zhao Chen, Jiquan Ngiam, Yanping Huang, Thang Luong, Henrik Kretzschmar, Yuning Chai, Dragomir Anguelov:
Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout. NeurIPS 2020 - [i21]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:
Improving 3D Object Detection through Progressive Population Based Augmentation. CoRR abs/2004.00831 (2020) - [i20]Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, Henrik Kretzschmar:
SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving. CoRR abs/2005.03844 (2020) - [i19]Zhishuai Zhang, Jiyang Gao, Junhua Mao, Yukai Liu, Dragomir Anguelov, Congcong Li:
STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction. CoRR abs/2005.04255 (2020) - [i18]Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Congcong Li, Cordelia Schmid:
VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation. CoRR abs/2005.04259 (2020) - [i17]Alex Bewley, Pei Sun, Thomas Mensink
, Dragomir Anguelov, Cristian Sminchisescu:
Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection. CoRR abs/2005.09927 (2020) - [i16]Wei-Chih Hung, Henrik Kretzschmar, Tsung-Yi Lin, Yuning Chai, Ruichi Yu, Ming-Hsuan Yang, Dragomir Anguelov:
SoDA: Multi-Object Tracking with Soft Data Association. CoRR abs/2008.07725 (2020) - [i15]Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, Congcong Li, Dragomir Anguelov:
TNT: Target-driveN Trajectory Prediction. CoRR abs/2008.08294 (2020) - [i14]Zhao Chen, Jiquan Ngiam, Yanping Huang, Thang Luong, Henrik Kretzschmar, Yuning Chai, Dragomir Anguelov:
Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout. CoRR abs/2010.06808 (2020)
2010 – 2019
- 2019
- [c23]Yuning Chai, Benjamin Sapp, Mayank Bansal, Dragomir Anguelov:
MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction. CoRL 2019: 86-99 - [c22]Yin Zhou, Pei Sun, Yu Zhang, Dragomir Anguelov, Jiyang Gao, Tom Ouyang, James Guo, Jiquan Ngiam, Vijay Vasudevan:
End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds. CoRL 2019: 923-932 - [i13]Yuning Chai, Benjamin Sapp, Mayank Bansal, Dragomir Anguelov:
MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction. CoRR abs/1910.05449 (2019) - [i12]Yin Zhou, Pei Sun, Yu Zhang, Dragomir Anguelov, Jiyang Gao, Tom Ouyang, James Guo, Jiquan Ngiam, Vijay Vasudevan:
End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds. CoRR abs/1910.06528 (2019) - [i11]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:
Scalability in Perception for Autonomous Driving: Waymo Open Dataset. CoRR abs/1912.04838 (2019) - 2018
- [c21]Danfei Xu, Dragomir Anguelov, Ashesh Jain:
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation. CVPR 2018: 244-253 - 2017
- [c20]Arsalan Mousavian, Dragomir Anguelov, John Flynn, Jana Kosecka:
3D Bounding Box Estimation Using Deep Learning and Geometry. CVPR 2017: 5632-5640 - [i10]Danfei Xu, Dragomir Anguelov, Ashesh Jain:
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation. CoRR abs/1711.10871 (2017) - 2016
- [c19]Wei Liu, Dragomir Anguelov, Dumitru Erhan
, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, Alexander C. Berg:
SSD: Single Shot MultiBox Detector. ECCV (1) 2016: 21-37 - [c18]Loris Bazzani, Alessandro Bergamo, Dragomir Anguelov, Lorenzo Torresani:
Self-taught object localization with deep networks. WACV 2016: 1-9 - [i9]Arsalan Mousavian, Dragomir Anguelov, John Flynn, Jana Kosecka:
3D Bounding Box Estimation Using Deep Learning and Geometry. CoRR abs/1612.00496 (2016) - 2015
- [c17]Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan
, Vincent Vanhoucke, Andrew Rabinovich:
Going deeper with convolutions. CVPR 2015: 1-9 - [c16]Scott E. Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich:
Training Deep Neural Networks on Noisy Labels with Bootstrapping. ICLR (Workshop) 2015 - [c15]David Warde-Farley, Andrew Rabinovich, Dragomir Anguelov:
Self-informed neural network structure learning. ICLR (Workshop) 2015 - [i8]Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott E. Reed, Cheng-Yang Fu, Alexander C. Berg:
SSD: Single Shot MultiBox Detector. CoRR abs/1512.02325 (2015) - 2014
- [c14]Xiangxin Zhu, Dragomir Anguelov, Deva Ramanan
:
Capturing Long-Tail Distributions of Object Subcategories. CVPR 2014: 915-922 - [c13]Dumitru Erhan
, Christian Szegedy, Alexander Toshev, Dragomir Anguelov:
Scalable Object Detection Using Deep Neural Networks. CVPR 2014: 2155-2162 - [i7]Alessandro Bergamo, Loris Bazzani, Dragomir Anguelov, Lorenzo Torresani:
Self-taught Object Localization with Deep Networks. CoRR abs/1409.3964 (2014) - [i6]Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich:
Going Deeper with Convolutions. CoRR abs/1409.4842 (2014) - [i5]Christian Szegedy, Scott E. Reed, Dumitru Erhan, Dragomir Anguelov:
Scalable, High-Quality Object Detection. CoRR abs/1412.1441 (2014) - 2013
- [i4]Dragomir Anguelov, Rahul Biswas, Daphne Koller, Benson Limketkai, Sebastian Thrun:
Learning Hierarchical Object Maps Of Non-Stationary Environments with mobile robots. CoRR abs/1301.0551 (2013) - [i3]Daphne Koller, Uri Lerner, Dragomir Anguelov:
A General Algorithm for Approximate Inference and its Application to Hybrid Bayes Nets. CoRR abs/1301.6709 (2013) - [i2]Dumitru Erhan, Christian Szegedy, Alexander Toshev, Dragomir Anguelov:
Scalable Object Detection using Deep Neural Networks. CoRR abs/1312.2249 (2013) - 2012
- [i1]Dragomir Anguelov, Daphne Koller, Hoi-Cheung Pang, Praveen Srinivasan, Sebastian Thrun:
Recovering Articulated Object Models from 3D Range Data. CoRR abs/1207.4129 (2012) - 2010
- [j2]Dragomir Anguelov, Carole Dulong, Daniel Filip, Christian Früh, Stéphane Lafon, Richard Lyon, Abhijit S. Ogale, Luc Vincent, Josh Weaver:
Google Street View: Capturing the World at Street Level. Computer 43(6): 32-38 (2010) - [c12]Qi-Xing Huang, Dragomir Anguelov:
High quality pose estimation by aligning multiple scans to a latent map. ICRA 2010: 1353-1360 - [c11]Matthew Koichi Grimes, Dragomir Anguelov, Yann LeCun:
Hybrid hessians for flexible optimization of pose graphs. IROS 2010: 2997-3004
2000 – 2009
- 2008
- [c10]Kuang-chih Lee, Dragomir Anguelov, Baris Sumengen, Salih Burak Göktürk:
Markov random field models for hair and face segmentation. FG 2008: 1-6 - 2007
- [c9]Dragomir Anguelov, Kuang-chih Lee, Salih Burak Göktürk, Baris Sumengen:
Contextual Identity Recognition in Personal Photo Albums. CVPR 2007 - 2006
- [b1]Dragomir Anguelov:
Learning models of shape from 3D range data. Stanford University, USA, 2006 - [c8]Jim Rodgers, Dragomir Anguelov, Hoi-Cheung Pang, Daphne Koller:
Object Pose Detection in Range Scan Data. CVPR (2) 2006: 2445-2452 - 2005
- [j1]Dragomir Anguelov, Praveen Srinivasan, Daphne Koller, Sebastian Thrun, Jim Rodgers, James Davis:
SCAPE: shape completion and animation of people. ACM Trans. Graph. 24(3): 408-416 (2005) - [c7]Dragomir Anguelov, Benjamin Taskar, Vassil Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz, Andrew Y. Ng:
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data. CVPR (2) 2005: 169-176 - 2004
- [c6]Dragomir Anguelov, Daphne Koller, Evan Parker, Sebastian Thrun:
Detecting and Modeling Doors with Mobile Robots. ICRA 2004: 3777-3784 - [c5]Dragomir Anguelov, Praveen Srinivasan, Hoi-Cheung Pang, Daphne Koller, Sebastian Thrun, James Davis:
The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces. NIPS 2004: 33-40 - [c4]Dragomir Anguelov, Daphne Koller, Hoi-Cheung Pang, Praveen Srinivasan, Sebastian Thrun:
Recovering Articulated Object Models from 3D Range Data. UAI 2004: 18-26 - 2002
- [c3]Dragomir Anguelov, Rahul Biswas, Daphne Koller, Benson Limketkai, Sebastian Thrun:
Learning Hierarchical Object Maps of Non-Stationary Environments with Mobile Robots. UAI 2002: 10-17 - 2000
- [c2]Martin Gavrilov, Dragomir Anguelov, Piotr Indyk, Rajeev Motwani:
Mining the stock market (extended abstract): which measure is best? KDD 2000: 487-496
1990 – 1999
- 1999
- [c1]Daphne Koller, Uri Lerner, Dragomir Anguelov:
A General Algorithm for Approximate Inference and Its Application to Hybrid Bayes Nets. UAI 1999: 324-333
Coauthor Index
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